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Yoshiro Yamada
,
Subrena Harris
,
Michael Hayes
,
Rob Simpson
,
Werenfrid Wimmer
,
Raymond Holmes
,
Tim Nightingale
,
Arrow Lee
,
Nis Jepsen
,
Nicole Morgan
,
Frank-M. Göttsche
,
Raquel Niclòs
,
Martín Perelló
,
Craig Donlon
, and
Nigel Fox

Abstract

An international comparison of field deployed radiometers for sea surface skin temperature (SSTskin) retrieval was conducted in June 2022. The campaign comprised a laboratory and a field comparison. In the laboratory part the radiometers were compared against reference standard blackbodies, while the same was done with the blackbodies used for the calibration of the radiometers against a transfer standard radiometer. Reference values were provided by the National Physical Laboratory (NPL), traceable to the primary standard on the International Temperature Scale of 1990. This was followed by the field comparison at a seaside pier on the south coast of England, where the radiometers were compared against each other while viewing the closely adjacent surface of the sea. This paper reports the results of the laboratory comparison of radiometers and blackbodies.

For the blackbody comparison, the brightness temperature of the blackbody reported by the participants agreed with the reference value measured by the NPL transfer standard radiometer within the uncertainties for all temperatures and for all blackbodies. For the radiometer comparison, the temperature range of most interest from the SSTskin retrieval point of view is 10 °C to 30 °C, and in this temperature range, and up to the maximum comparison temperature of 50 °C, all participants’ reported results were in agreement with the reference. On the other hand, below 0 °C the reported values showed divergence from the reference and the differences exceeded the uncertainties. The divergence shows there is room for improvement in uncertainty estimation at lower temperatures, although it will have limited implication in the SSTskin retrieval.

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Yoshiro Yamada
,
Subrena Harris
,
Werenfrid Wimmer
,
Raymond Holmes
,
Tim Nightingale
,
Arrow Lee
,
Nis Jepsen
,
Nicole Morgan
,
Frank-M. Göttsche
,
Raquel Niclòs
,
Martín Perelló
,
Vicente Garcia-Santos
,
Craig Donlon
, and
Nigel Fox

Abstract

An international comparison of field-deployed radiometers for sea surface skin temperature (SSTskin) retrieval was conducted during two weeks in June 2022. The comparison comprised a laboratory comparison and a field comparison. The field comparison of the radiometers took place on the second week at a seaside pier on the south coast of England. Six thermal infrared radiometers were compared against each other while continuously viewing the closely adjacent surface of the sea from the end of the pier. This paper reports the results of this field comparison.

All participants’ radiometers agreed with the reference value, evaluated as the simple mean of the participant reported values, within the claimed uncertainties. The SSTskin variation during the five-day period was within 3 °C around 18.3 °C, which is two times larger in range than in the previous comparison in 2016, while the mean of the difference from the reference value over the period evaluated for each participant, was found to be within 0.07 °C, which is a two-times improvement on the previous results.

During the comparison an insignificant but noticeable abrupt shift in measured value occurred in one of the radiometers, which could not have been detected without comparison with other instruments. This demonstrated the effectiveness of having long term stable internal reference sources in the instrument, a feature this particular radiometer did not have.

The combined results from the laboratory comparison and the field comparison contribute to improve confidence in the retrieved SSTskin.

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Xinru Liu
,
Hang Jie
,
Yulin Zou
,
Shengjun Liu
,
Yamin Hu
,
Shuyi Liu
,
Dangfu Yang
,
Liang Zhao
, and
Jian He

Abstract

According to HadGEM3 (CMIP6) models, anthropogenic forcing reduced the probability of 2022-like June mean precipitation by about 32% (15%) and increased 5-day rainfall extreme probability by about 1.8 (1.3) times.

Open access
Bosi Sheng
,
Buwen Dong
,
Haolin Wang
,
Mingming Zhang
,
Shuheng Lin
,
Peng Si
,
Fraser C. Lott
, and
Qingxiang Li

Abstract

Precipitation in southern China during April–June 2022 was the highest since 1961. Anthropogenic forcing has reduced the probability of 2022-like Rx30day precipitation by about 45% based on CMIP6 simulations.

Open access
Fan Mei
,
Hailong Wang
,
Zihua Zhu
,
Damao Zhang
,
Qi Zhang
,
Jerome D. Fast
,
William I. Gustafson Jr.
,
Xiangyu Li
,
Beat Schmid
,
Christopher Niedek
,
Jason Tomlinson
, and
Connor Flynn

Abstract

The spatial distribution of ambient aerosol particles significantly impacts aerosol- radiation-cloud interactions, which contribute to the largest uncertainty in global anthropogenic radiative forcing estimations. However, the atmospheric boundary layer and lower free troposphere have not been adequately sampled in terms of spatiotemporal resolution, hindering a comprehensive characterization of various atmospheric processes and impeding our understanding of the Earth system. To address this research data gap, we have leveraged the development of uncrewed aerial systems (UAS) and advanced measurement techniques to obtain mesoscale spatial data on aerosol microphysical and optical properties around the U.S. Southern Great Plains (SGP) atmospheric observatory. Our study also benefits from state-of-the-art laboratory facilities that include 3-dimensional molecular imaging techniques enabled by secondary ion mass spectrometry and nanogram-level chemical composition analysis via micronebulization aerosol mass spectrometry.

Through our study, we have developed a framework for observation-modeling integration, enabling an examination of how various assumptions about the organic-inorganic components mixing state, inferred from chemical analysis, affect clouds and radiation in observation-constrained model simulations. By integrating observational constraints (derived from offline chemical analysis of the aerosol surface using collected samples) with in-situ UAS observations, we have identified a prominent role of organic-enriched nanometer layers located at the surface of aerosol particles in determining profiles of aerosol optical and hygroscopic properties over the SGP observatory. Furthermore, we have improved the agreement between predicted clouds and ground-based cloud lidar measurements. This UAS-model-laboratory integration exemplifies how these new advanced capabilities can significantly enhance our understanding of aerosol-radiation-cloud interactions.

Open access
Free access
Paolo Giani
and
Paola Crippa

Abstract

We present a new ensemble of 36 numerical experiments aimed at comprehensively gauging the sensitivity of nested Large Eddy Simulations (LES) driven by large scale dynamics. Specifically, we explore 36 multiscale configurations of the Weather Research and Forecasting (WRF) model to simulate the boundary layer flow over the complex topography at the Perdigão field site, with five nested domains discretized at horizontal resolutions ranging from 11.25 kilometers to 30 meters. Each ensemble member has a unique combination of the following input factors, (i) large-scale initial and boundary conditions, (ii) subgrid turbulence modeling in the gray zone of turbulence, (iii) subgrid-scale (SGS) models in LES simulations and (iv) topography and land cover datasets. We probe their relative importance for LES calculations of velocity, temperature and moisture fields. Variance decomposition analysis unravels large sensitivities to topography and land use datasets and very weak sensitivity to the LES SGS model. Discrepancies within ensemble members can be as large as 2.5 m s−1 for the time-averaged near-surface wind speed on the ridge, and as large as 10 m s−1 without time averaging. At specific time points, a large fraction of this sensitivity can be explained by the different turbulence models in the gray zone domains. We implement a horizontal momentum and moisture budget routine in WRF to further elucidate the mechanisms behind the observed sensitivity, paving the way for an increased understanding of the tangible effects of the gray zone of turbulence problem.

Restricted access
Xin Xu
,
Rongrong Zhang
,
Miguel A. C. Teixeira
,
Annelize van Niekerk
,
Ming Xue
,
Yixiong Lu
,
Haile Xue
,
Runqiu Li
, and
Yuan Wang

Abstract

The momentum transport by orographic gravity waves (OGWs) plays an important role in driving the large-scale circulation throughout the atmosphere and is subject to parameterization in numerical models. Current parameterization schemes, which were originally developed for coarse-resolution models, commonly assume that unresolved OGWs are hydrostatic. With the increase in the horizontal resolution of state-of-the-art numerical models, unresolved OGWs are of smaller horizontal scale and more influenced by nonhydrostatic effects (NHE), thus challenging use of the hydrostatic assumption. Based on the analytical formulae for nonhydrostatic OGWs derived in our recent study, the orographic gravity wave drag (OGWD) parameterization scheme in the Model for Prediction Across Scales is revised by accounting for NHE. Global simulations with 30-km horizontal resolution are conducted to investigate NHE on the momentum transport of OGWs and their impacts on the large-scale circulation in boreal winter. NHE are evident in regions of complex terrain such as the Tibetan Plateau, Rocky Mountains, Southern Andes and Eastern Antarctica. The parameterized surface wave momentum flux can be either reduced or enhanced depending on the relative importance of NHE and model physics-dynamics interactions. The NHE corrections to the OGWD scheme significantly reduce the easterly biases in the polar stratosphere of the Northern Hemisphere, due to both weakened OGWD in the upper troposphere and lower stratosphere and suppressed upward propagation of resolved waves into the stratosphere. However, the revised OGWD scheme only has a weak influence on the large-scale circulation in the Southern Hemisphere during boreal winter.

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Maité Morales-Medina
,
Ana P. Ortíz-Martínez
,
Cynthia M. Pérez-Cardona
,
Digna Rueda-Roa
,
Daniel Otis
,
Edgar Pérez-Matías
,
Frank Muller-Karger
,
Olga Mayol-Bracero
, and
Pablo Méndez-Lázaro

Abstract

An extreme Saharan dust storm (named Godzilla) arrived to the Caribbean region in June 2020, deteriorating the air quality to hazardous levels and unhealthy conditions for sensitive groups of people. Our main objective was to characterize populations at risk for Saharan Dust by analyzing distribution and levels of dust events in Puerto Rico, and by conducting an online survey to assess community perceptions on Saharan Dust health effects. Three daily satellite aerosols products from 2013 to 2020 were retrieved from the Visible Infrared Imaging Radiometer Suite over Puerto Rico to better understand the patterns, frequency, and seasonality of aerosols. The atmospheric results indicated that extreme values (>99th) of big size aerosols (e.g. Sahara dust) were observed over Puerto Rico on June 22, 2020. A total of 1,504 qualified people participated in the survey during the summer of 2020, and it was analyzed with descriptive statistics, frequency analysis, and chi-square tests. 51% of the survey participants were on the age group of 25-44 years old, and 65% of the participants had at least one pre-existing health condition (respiratory diseases 27%; cardiovascular diseases 28%). Nearly 90% of the participants indicated that Saharan dust affected the health status of both the respondents and their family members. Irritation of eyes (22%), nose (24%), and throat (23%), as well as breathing difficulties (10%) were the most common symptoms reported. Understanding patients’ health profiles associated with Saharan dust is essential before developing public health strategies to minimize exacerbation of health conditions in Puerto Rico.

Restricted access
Amanda Richter
and
Timothy J. Lang

Abstract

NASA’s Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign gathered data using “satellite-simulating” (albeit with higher-resolution data than satellites currently provide) and in situ aircraft to study snowstorms, with an emphasis on banding. This study used three IMPACTS microwave instruments—two passive and one active—chosen for their sensitivity to precipitation microphysics. The 10–37-GHz passive frequencies were well suited for detecting light precipitation and differentiating rain intensities over water. The 85–183-GHz frequencies were more sensitive to cloud ice, with higher cloud tops manifesting as lower brightness temperatures, but this did not necessarily correspond well to near-surface precipitation. Over land, retrieving precipitation information from radiometer data is more difficult, requiring increased reliance on radar to assess storm structure. A dual-frequency ratio (DFR) derived from the radar’s Ku- and Ka-band frequencies provided greater insight into storm microphysics than reflectivity alone. Areas likely to contain mixed-phase precipitation (often the melting layer/bright band) generally had the highest DFR, and high-altitude regions likely to contain ice usually had the lowest DFR. The DFR of rain columns increased toward the ground, and snowbands appeared as high-DFR anomalies.

Significance Statement

Winter precipitation was studied using three airborne microwave sensors. Two were passive radiometers covering a broad range of frequencies, while the other was a two-frequency radar. The radiometers did a good job of characterizing the horizontal structure of winter storms when they were over water, but struggled to provide detailed information about winter storms when they were over land. The radar was able to provide vertically resolved details of storm structure over land or water, but only provided information at nadir, so horizontal structure was less well described. The combined use of all three instruments compensated for individual deficiencies, and was very effective at characterizing overall winter storm structure.

Open access