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Pavlos Kollias
,
Greg M. McFarquhar
,
Eric Bruning
,
Paul J. DeMott
,
Matthew R. Kumjian
,
Paul Lawson
,
Zachary Lebo
,
Timothy Logan
,
Kelly Lombardo
,
Mariko Oue
,
Greg Roberts
,
Raymond A. Shaw
,
Susan C. van den Heever
,
Mengistu Wolde
,
Kevin R. Barry
,
David Bodine
,
Roelof Bruintjes
,
Venkatachalam Chandrasekar
,
Andrew Dzambo
,
Thomas C. J. Hill
,
Michael Jensen
,
Francesc Junyent
,
Sonia M. Kreidenweis
,
Katia Lamer
,
Edward Luke
,
Aaron Bansemer
,
Christina McCluskey
,
Leonid Nichman
,
Cuong Nguyen
,
Ryan J. Patnaude
,
Russell J. Perkins
,
Heath Powers
,
Keyvan Ranjbar
,
Eric Roux
,
Jeffrey Snyder
,
Bernat P. Treserras
,
Peisang Tsai
,
Nathan A. Wales
,
Cory Wolff
,
Nithin Allwayin
,
Ben Ascher
,
Jason Barr
,
Yishi Hu
,
Yongjie Huang
,
Miles Litzmann
,
Zackary Mages
,
Katherine McKeown
,
Saurabh Patil
,
Elise Rosky
,
Kristofer Tuftedal
,
Min-Duan Tzeng
, and
Zeen Zhu

Abstract

Convective clouds play an important role in the Earth’s climate system and are a known source of extreme weather. Gaps in our understanding of convective vertical motions, microphysics, and precipitation across a full range of aerosol and meteorological regimes continue to limit our ability to predict the occurrence and intensity of these cloud systems. Towards improving predictability, the National Science Foundation (NSF) sponsored a large field experiment entitled “Experiment of Sea Breeze Convection, Aerosols, Precipitation, and Environment (ESCAPE).” ESCAPE took place between 30 May - 30 Sept. 2022 in the vicinity of Houston, TX because this area frequently experiences isolated deep convection that interacts with the region's mesoscale circulations and its range of aerosol conditions.

ESCAPE focused on collecting observations of isolated deep convection through innovative sampling, and on developing novel analysis techniques. This included the deployment of two research aircraft, the National Research Council of Canada Convair-580 and the Stratton Park Engineering Company Learjet, which combined conducted 24 research flights from 30 May to 17 June. On the ground, three mobile X-band radars, and one mobile Doppler lidar truck equipped with soundings, were deployed from 30 May to 28 June. From 1 August to 30 Sept. 2022, a dual-polarization C-band radar was deployed and operated using a novel, multi-sensor agile adaptive sampling strategy to track the entire lifecycle of isolated convective clouds. Analysis of the ESCAPE observations has already yielded preliminary findings on how aerosols and environmental conditions impact the convective life cycle.

Open access
Melanie A. Schroers
,
Ty A. Dickinson
,
Paulina Ćwik
,
Renee A. McPherson
, and
Elinor R. Martin

Abstract

Extreme precipitation over a two-week period can cause significant impacts to life and property. Trustworthy and easy-to-understand forecasts of these extreme periods on the subseasonal-to-seasonal timeframe may provide additional time for planning. The Prediction of Rainfall Extremes at Subseasonal to Seasonal Periods (PRES2iP) project team conducted three workshops over six years to engage with stakeholders to learn what is needed for decision-making for subseasonal precipitation. In this study experimental subseasonal to seasonal (S2S) forecast products were designed, using knowledge gained from previous stakeholder workshops, and shown to decision-makers to evaluate the products for two 14-day extreme precipitation period scenarios. Our stakeholders preferred a combination of products that covered the spatial extent, regional daily values, with associated uncertainty, and text narratives with anticipated impacts for planning within the S2S timeframe. When targeting longer extremes, having information regarding timing of expected impacts was seen as crucial for planning. We found that there is increased uncertainty tolerance with stakeholders when using products at longer lead times that typical skill metrics, such as critical success index or anomaly correlation coefficient, do not capture. Therefore, the use of object-oriented verification, that allows for more flexibility in spatial uncertainty, might be beneficial for evaluating S2S forecasts. These results help to create a foundation for design, verification, and implementation of future operational forecast products with longer lead times, while also providing an example for future workshops that engage both researchers and decision-makers.

Open access
Mark Govett
,
Bubacar Bah
,
Peter Bauer
,
Dominique Berod
,
Veronique Bouchet
,
Susanna Corti
,
Chris Davis
,
Yihong Duan
,
Tim Graham
,
Yuki Honda
,
Adrian Hines
,
Michel Jean
,
Junishi Ishida
,
Bryan Lawrence
,
Jian Li
,
Juerg Luterbacher
,
Chiasi Muroi
,
Kris Rowe
,
Martin Schultz
,
Martin Visbeck
, and
Keith Williams

Abstract

The emergence of exascale computing and artificial intelligence offer tremendous potential to significantly advance earth system prediction capabilities. However, enormous challenges must be overcome to adapt models and prediction systems to use these new technologies effectively. A recent WMO report on exascale computing recommends “urgency in dedicating efforts and attention to disruptions associated with evolving computing technologies that will be increasingly difficult to overcome, threatening continued advancements in weather and climate prediction capabilities. Further, the explosive growth in data from observations, model and ensemble output, and post processing threatens to overwhelm the ability to deliver timely, accurate, and precise information needed for decision making. AI offers untapped opportunities to alter how models are developed, observations are processed, and predictions are analyzed and extracted for decision-making. Given the extraordinarily high cost of computing, growing complexity of prediction systems and increasingly unmanageable amount of data being produced and consumed, these challenges are rapidly becoming too large for any single institution or country to handle. This paper describes key technical, and budgetary challenges, identifies gaps and ways to address them, and makes a number of recommendations.

Open access
Yihan Du
,
Tianxing Wang
,
Yu Zhou
,
Husi Letu
,
Dahui Li
, and
Yuyang Xian

Abstract

Longwave downward radiation (LWDR) is an important driving parameter in climate and hydrological models. Compared to traditional ground-based measurements, remote sensing has unique advantages in estimating global LWDR. However, for current remote sensing missions, as the typical available satellite-derived LWDR product with global coverage and hourly temporal resolution, the Clouds and the Earth’s Radiant Energy System-Synoptic (CERES-SYN) top of atmosphere and surface fluxes and clouds has a low spatial resolution (1° × 1°). There is still much room for improvement of the existing remote sensing LWDR products in terms of accuracy, spatiotemporal resolutions, and the ability to explain and quantify the changes of longwave radiation at various scales. To overcome these limitations, this paper developed a new global LWDR product with improved accuracy (the RMSE < 30 W/m2 over the globe), high temporal resolution (hourly), and spatial resolution (5 km) based on Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. It serves as a LWDR product within the Long-term Earth System spatiotemporally Seamless Radiation budget dataset (referred to as LessRad). As the first long-term high-resolution, spatiotemporally continuous LWDR product (2002-2022, 1 h, 5 km), the LessRad reveals its advantages in studying the spatiotemporal variability of LWDR on finer scales. It also provides a valuable data source for various applications, such as analyzing land-atmosphere interactions and quantifying climate feedback, and thus, is potentially helpful for understanding the earth’s energy budget and dynamics.

Open access
Jonghun Kam
,
Seung-Ki Min
,
Byeong-Hee Kim
,
Yeon-Hee Kim
,
Leandro B. Diaz
,
Jong-Seong Kug
, and
Rokjin Park

CMIP6 simulations showed a weak human contribution to 2022-like Central Andes spring droughts, due to compensating impacts between anthropogenic greenhouse gases and aerosols.

Open access
J. Vilà-Guerau de Arellano
,
O. K. Hartogensis
,
H. de Boer
,
R. Moonen
,
R. González-Armas
,
M. Janssens
,
G. A. Adnew
,
D. J. Bonell-Fontás
,
S. Botía
,
S. P. Jones
,
H. van Asperen
,
S. Komiya
,
V. S. de Feiter
,
D. Rikkers
,
S. de Haas
,
L. A. T. Machado
,
C. Q. Dias-Junior
,
G. Giovanelli-Haytzmann
,
W. I. D. Valenti
,
R. C. Figueiredo
,
C. S. Farias
,
D. H. Hall
,
A. C. S. Mendonça
,
F. A. G. da Silva
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J. L. Marton da Silva
,
R. Souza
,
G. Martins
,
J. N. Miller
,
W. B. Mol
,
B. Heusinkveld
,
C. C. van Heerwaarden
,
F. A. F. D’Oliveira
,
R. Rodrigues Ferreira
,
R. Acosta Gotuzzo
,
G. Pugliese
,
J. Williams
,
A. Ringsdorf
,
A. Edtbauer
,
C. A. Quesada
,
B. Takeshi Tanaka Portela
,
E. Gomes Alves
,
C. Pöhlker
,
S. Trumbore
,
J. Lelieveld
, and
T. Röckmann

Abstract

How are rainforest photosynthesis and turbulent fluxes influenced by clouds? To what extent are clouds affected by local processes driven by rainforest energy, water and carbon fluxes? These interrelated questions were the main drivers of the intensive field experiment CloudRoots-Amazon22 which took place at the ATTO/Campina supersites in the Amazon rainforest during the dry season, in August 2022. CloudRoots-Amazon22 collected observational data to derive cause-effect relationships between processes occurring at the leaf-level up to canopy scales in relation to the diurnal evolution of the clear-to-cloudy transition. First, we studied the impact of cloud and canopy radiation perturbations on the sub-diurnal variability of stomatal conductance. Stoma opening is larger in the morning, modulated by the cloud optical thickness. Second, we combined 1 Hz-frequency measurements of the stable isotopologues of carbon dioxide and water vapor with measurements of turbulence to determine carbon dioxide and water vapor sources and sinks within the canopy. Using scintillometer observations, we inferred 1-minute sensible heat flux that responded within minutes to the cloud passages. Third, collocated profiles of state variables and greenhouse gases enabled us to determine the role of clouds in vertical transport. We then inferred, using canopy and upper-atmospheric observations and a parameterization, the cloud cover and cloud mass flux to establish causality between canopy and cloud processes. This shows the need of comprehensive observational set to improve weather and climate model representations. Our findings contribute to advance our knowledge of the coupling between cloudy boundary layers and primary carbon productivity of the Amazon rainforest.

Open access
Paolo Laj
,
Cathrine Lund Myhre
,
Véronique Riffault
,
Vassilis Amiridis
,
Hendrik Fuchs
,
Konstantinos Eleftheriadis
,
Tuukka Petäjä
,
Thérèse Salameh
,
Niku Kivekäs
,
Eija Juurola
,
Giulia Saponaro
,
Sabine Philippin
,
Carmela Cornacchia
,
Lucas Alados Arboledas
,
Holger Baars
,
Anja Claude
,
Martine De Mazière
,
Bart Dils
,
Marvin Dufresne
,
Nikolaos Evangeliou
,
Olivier Favez
,
Markus Fiebig
,
Martial Haeffelin
,
Hartmut Herrmann
,
Kristina Höhler
,
Niklas Illmann
,
Axel Kreuter
,
Elke Ludewig
,
Eleni Marinou
,
Ottmar Möhler
,
Lucia Mona
,
Lise Eder Murberg
,
Doina Nicolae
,
Anna Novelli
,
Ewan O'Connor
,
Kevin Ohneiser
,
Rosa Maria Petracca Altieri
,
Bénédicte Picquet-Varrault
,
Dominik van Pinxteren
,
Bernhard Pospichal
,
Jean-Philippe Putaud
,
Stefan Reimann
,
Nikolaos Siomos
,
Iwona Stachlewska
,
Ralf Tillmann
,
Kalliopi Artemis Voudouri
,
Ulla Wandinger
,
Alfred Wiedensohler
,
Arnoud Apituley
,
Adolfo Comerón
,
Martin Gysel-Beer
,
Nikolaos Mihalopoulos
,
Nina Nikolova
,
Aleksander Pietruczuk
,
Stéphane Sauvage
,
Jean Sciare
,
Henrik Skov
,
Tove Svendby
,
Erik Swietlicki
,
Dimitar Tonev
,
Geraint Vaughan
,
Vladimir Zdimal
,
Urs Baltensperger
,
Jean-François Doussin
,
Markku Kulmala
,
Gelsomina Pappalardo
,
Sanna Sorvari Sundet
, and
Milan Vana

Abstract

The Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) officially became the 33rd European Research Infrastructure Consortium (ERIC) on April 25, 2023 with the support of 17 founding member and observer countries. As a pan-European legal organization, ACTRIS ERIC will coordinate the provision of data and data products on short-lived atmospheric constituents and clouds relevant to climate and air pollution over the next 15-20 years. ACTRIS was designed more than a decade ago, and its development was funded at national and European levels. It was included in the European Strategy Forum on Research Infrastructures (ESFRI) Roadmap in 2016 and subsequently, in the national infrastructure roadmaps of European countries. It became a landmark of the ESFRI roadmap in 2021. The purpose of this paper is to describe the mission of ACTRIS, its added value to the community of atmospheric scientists, providing services to academia as well as the public and private sectors, and to summarize its main achievements. The present publication serves as a reference document for ACTRIS, its users and the scientific community as a whole. It provides the reader with relevant information and an overview on ACTRIS governance and services, as well as a summary of the main scientific achievements of the last 20 years. The paper concludes with an outlook on the upcoming challenges for ACTRIS and the strategy for its future evolution.

Open access
L. M. Beal
,
J. Vialard
,
M. K. Roxy
,
J. Li
,
M. Andres
,
H. Annamalai
,
M. Feng
,
W. Han
,
R. Hood
,
T. Lee
,
M. Lengaigne
,
R. Lumpkin
,
Y. Masumoto
,
M. J. McPhaden
,
M. Ravichandran
,
T. Shinoda
,
B. M. Sloyan
,
P. G. Strutton
,
A. C. Subramanian
,
T. Tozuka
,
C. C. Ummenhofer
,
A. S. Unnikrishnan
,
J. Wiggert
,
L. Yu
,
L. Cheng
,
D. G. Desbruyères
, and
V. Parvathi
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