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Shoobhangi Tyagi
,
Sandeep Sahany
,
Dharmendra Saraswat
,
Saroj Kanta Mishra
,
Amlendu Dubey
, and
Dev Niyogi

Abstract

The 2015 Paris Agreement outlined limiting global warming to 1.5°C relative to the preindustrial levels, necessitating the development of regional climate adaptation strategies. This requires a comprehensive understanding of how the 1.5°C rise in global temperature would translate across different regions. However, its implications on critical agricultural components, particularly blue and green water, remains understudied. This study investigates these changes using a rice-growing semiarid region in central India. The aim of this study is to initiate a discussion on the regional response of blue–green water at specific warming levels. Using different global climate models (GCMs) and shared socioeconomic pathways (SSPs), the study estimated the time frame for reaching the 1.5°C warming level and subsequently investigated changes in regional precipitation, temperature, surface runoff, and blue–green water. The results reveal projected reductions in precipitation and surface runoff by approximately 5%–15% and 10%–35%, respectively, along with decrease in green and blue water by approximately 12%–1% and 40%–10%, respectively, across different GCMs and SSPs. These findings highlight 1) the susceptibility of blue–green water to the 1.5°C global warming level, 2) the narrow time frame available for the region to develop the adaptive strategies, 3) the influence of warm semiarid climate on the blue–green water dynamics, and 4) the uncertainty associated with regional assessment of a specific warming level. This study provides new insights for shaping food security strategies over highly vulnerable semiarid regions and is expected to serve as a reference for other regional blue/green water assessment studies.

Significance Statement

This study helps to drive home the message that a global agreement to limit the warming level to 1.5°C does not mean local-scale temperature (and associated hydrological) impacts would be limited to those levels. The regional changes can be more exaggerated and uncertain, and they also depend on the choice of the climate model and region. Therefore, local-scale vulnerability assessments must focus on the multidimensional assessment of a 1.5°C warmer world involving different climate models, climate-sensitive components, and regions. This information is relevant for managing vulnerable agricultural systems. This study is among the first to investigate the critical agricultural components such as the blue–green water over a semiarid Indian region, and the findings and methodology are expected to be transferable for performing regional-scale assessments elsewhere.

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Martin P. Hoerling
,
Jon K. Eischeid
,
Henry F. Diaz
,
Balaji Rajagopolan
, and
Eric Kuhn

Abstract

Of concern to Colorado River management, as operating guidelines post-2026 are being considered, is whether water resource recovery from low flows during 2000–2020 is possible. Here we analyze new simulations from the sixth generation of the Coupled Model Intercomparison Project (CMIP6) to determine plausible climate impacts on Colorado River flows for 2026–2050 when revised guidelines would operate. We constrain projected flows for Lee Ferry, the gauge through which 85% of the river flow passes, using its estimated sensitivity to meteorological variability together with CMIP6 projected precipitation and temperature changes. The critical importance of precipitation, especially its natural variability, is emphasized. Model projections indicate increased precipitation in the Upper Colorado River basin due to climate change, which alone increases river flows 5%–7% (relative to a 2000–2020 climatology). Depending on the river’s temperature sensitivity, this wet signal compensates some, if not all, of the depleting effects from basin warming. Considerable internal decadal precipitation variability (~5% of the climatological mean) is demonstrated, driving a greater range of plausible Colorado River flow changes for 2026–2050 than previously surmised from treatment of temperature impacts alone: the overall precipitation-induced Lee Ferry flow changes span −25% to +40% contrasting with a −30% to −5% range from expected warming effects only. Consequently, extreme low and high flows are more likely. Lee Ferry flow projections, conditioned on initial drought states akin to 2000–2020, reveal substantial recovery odds for water resources, albeit with elevated risks of even further flow declines than in recent decades.

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Yusen Yuan
,
Lixin Wang
,
Zhongwang Wei
,
Hoori Ajami
,
Honglang Wang
, and
Taisheng Du

Abstract

The isotopic composition of evapotranspiration δ ET is a crucial parameter in isotope-based evapotranspiration (ET) partitioning and moisture recycling studies. The Keeling plot method is the most prevalent method to calculate δ ET, though it contains large extrapolated uncertainties from the least squares regression. Traditional Keeling regression uses the mean point of individual measurements. Here, a modified Keeling plot framework was proposed using the median point of individual measurements. We tested the δ ET uncertainty using the mean point [σ ET (mean)] and median point [σ ET (median)]. Multiple resolutions of input and output data from six independent sites were used to test the performance of the two methods. The σ ET (mean) would be greater than σ ET (median) when the mean value of inverse vapor concentration ( 1 / C υ ¯ ) is greater than the median value of inverse vapor concentration [ 1 / C υ ( median ) ]. When applying the filter of r 2 > 0.8, around 70% of σ ET (mean) was greater than σ ET (median). This phenomenon might be due to the normality of the vapor concentration Cυ producing the asymmetric distribution of 1/Cυ . The median method could perform significantly better than the mean method when inputting high-resolution measurements (e.g., 1 Hz) and when the water vapor concentration Cυ is relatively low. Compared to the mean method, applying the median method could on average reduce 6.88% of ET partitioning uncertainties and could on average reduce 9.00% of moisture recycling uncertainties. This study provided a new insight of the Keeling plot method and emphasized handling model output uncertainty from multiple perspectives instead of only from input parameters.

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Travis Griggs
,
James Flynn
,
Yuxuan Wang
,
Sergio Alvarez
,
Michael Comas
, and
Paul Walter

Abstract

Photochemical modeling outputs showing high ozone concentrations over the Gulf of Mexico and Galveston Bay during ozone episodes in the Houston–Galveston–Brazoria (HGB) region have not been previously verified using in situ observations. Such data were collected systematically, for the first time, from July to October 2021 from three boats deployed for the Galveston Offshore Ozone Observations (GO3) and Tracking Aerosol Convection Interactions Experiment—Air Quality (TRACER-AQ) field campaigns. A pontoon boat and a commercial vessel operated in Galveston Bay, while another commercial vessel operated in the Gulf of Mexico offshore of Galveston. All three boats had continuously operating sampling systems that included ozone analyzers and weather stations, and the two boats operating in Galveston Bay had a ceilometer. The sampling systems operated autonomously on the two commercial boats as they traveled their daily routes. Thirty-seven ozonesondes were launched over water on forecast high ozone days in Galveston Bay and the Gulf of Mexico. During the campaigns, multiple periods of ozone exceeding 100 ppbv were observed over water in Galveston Bay and the Gulf of Mexico. These events included previously identified conditions for high ozone events in the HGB region, such as the bay/sea-breeze recirculation and postfrontal environments, as well as a localized coastal high ozone event after the passing of a tropical system (Hurricane Nicholas) that was not well forecast.

Open access
Morgan E O’Neill
and
Daniel R. Chavas
Open access
Teryn J. Mueller
,
Christina M. Patricola
, and
Emily Bercos-Hickey

Abstract

The El Niño–Southern Oscillation (ENSO) influences seasonal Atlantic tropical cyclone (TC) activity by impacting environmental conditions important for TC genesis. However, the influence of future climate change on the teleconnection between ENSO and Atlantic TCs is uncertain, as climate change is expected to impact both ENSO and the mean climate state. We used the Weather Research and Forecasting model on a tropical channel domain to simulate 5-member ensembles of Atlantic TC seasons in historical and future climates under different ENSO conditions. Experiments were forced with idealized sea-surface temperature configurations based on the Community Earth System Model (CESM) Large Ensemble representing: a monthly-varying climatology, Eastern Pacific El Niño, Central Pacific El Niño, and La Niña. The historical simulations produced fewer Atlantic TCs during Eastern Pacific El Niño compared to Central Pacific El Niño, consistent with observations and other modeling studies. For each ENSO state, the future simulations produced a similar teleconnection with Atlantic TCs as in the historical simulations. Specifically, La Niña continues to enhance Atlantic TC activity, and El Niño continues to suppress Atlantic TCs, with greater suppression during Eastern Pacific El Niño compared to Central Pacific El Niño. In addition, we found a decrease in Atlantic TC frequency in the future relative to historical regardless of ENSO state, which was associated with a future increase in northern tropical Atlantic vertical wind shear and a future decrease in the zonal tropical Pacific SST gradient, corresponding to a more El Niño-like mean climate state. Our results indicate that ENSO will remain useful for seasonal Atlantic TC prediction in the future.

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Jingjie Yu
,
Bolan Gan
,
Haiyuan Yang
,
Zhaohui Chen
,
Lixiao Xu
, and
Lixin Wu

Abstract

Subtropical mode water (STMW) is a thick layer of water mass characterized by homogeneous properties within the main pycnocline, important for oceanic oxygen utilization, carbon sequestration, and climate regulation. North Pacific STMW is formed in the Kuroshio Extension region, where vigorous mesoscale eddies strongly interact with the atmosphere. However, it remains unknown how such mesoscale ocean-atmosphere (MOA) coupling affects the STMW formation. By conducting twin simulations with an eddy-resolving global climate model, we find that approximately 25% more STMW is formed with the MOA coupling than without it. This is attributable to a significant increase in ocean latent heat release primarily driven by higher wind speed over the STMW formation region, which is associated with the southward deflection of storm tracks in response to oceanic mesoscale imprints. Such enhanced surface latent heat loss overwhelms the stronger upper-ocean restratification induced by vertical eddy and turbulent heat transport, leading to the formation of colder and denser STMW in the presence of MOA coupling. Further investigation of a multi-model and multi-resolution ensemble of global coupled models reveals that the agreement between the STMW simulation in eddy-present/rich coupled models and observations is superior to that of eddy-free ones, likely due to more realistic representation of MOA coupling. However, the ocean-alone model simulations show significant limitations in improving STMW production, even with refined model resolution. This indicates the importance of incorporating the MOA coupling into Earth system models to alleviate biases in STMW and associated climatic and biogeochemical impacts.

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Jannick Fischer
,
Johannes M. L. Dahl
,
Brice E. Coffer
,
Jana Lesak Houser
,
Paul M. Markowski
,
Matthew D. Parker
,
Christopher C. Weiss
, and
Alex Schueth

Abstract

Over the last decade, supercell simulations and observations with ever increasing resolution have provided new insights into the vortex-scale processes of tornado formation. This article incorporates these and other recent findings into the existing three-step model by adding an additional fourth stage. The goal is to provide an updated and clear picture of the physical processes occurring during tornadogenesis. Specifically, we emphasize the importance of the low-level wind shear and mesocyclone for tornado potential, the organization and interaction of relatively small-scale pre-tornadic vertical vorticity maxima, and the transition to a tornado-characteristic flow. Based on these insights, guiding research questions are formulated for the decade ahead.

Open access
Hui Yu
,
Guomin Chen
,
Wai-Kin Wong
,
Jonathan L. Vigh
,
Chi-kin Pan
,
Xiaoqin Lu
,
Jun A. Zhang
,
Jie Tang
,
Kun Zhao
,
Peiyan Chen
,
Zifeng Yu
,
Mengqi Yang
,
Jason Dunion
,
Zheqing Fang
,
Xiaotu Lei
,
Ajit Tyagi
, and
Lianshou Chen

Abstract

The Typhoon Landfall Forecast Demonstration Project (TLFDP) (2010–2022) was an international cooperative scientific project conducted under the framework of the WMO. The primary objectives of the TLFDP were to enhance the capability of tropical cyclone (TC) forecasters, and support related decision-makers in effective utilization of the most advanced forecasting techniques for the ultimate purpose of reducing and preventing disasters associated with TC landfall. Forty agencies/organizations/projects globally participated in the activities of the TLFDP following its inception in 2010, although the primary focus was on landfalling TCs in the western North Pacific. The TLFDP facilitated collaborations and workshops that realized notable achievements in four key areas: 1) the collection, production, and sharing of TC data; 2) the development and application of TC forecast verification metrics; 3) research on TC forecast skill; and 4) development of new techniques for TC forecasting. An obvious outcome was the shift from prediction of TC features, including track and intensity, toward prediction of TC impacts with more probabilistic conception. The final years of the project also promoted increasing application of artificial intelligence and machine learning techniques in various techniques for analysis and forecasting of TCs. Although the TLFDP ended in 2022, its core activities have continued to be extended through new WMO projects and regional cooperative initiatives.

Open access
Christopher J. Schultz
,
Phillip M. Bitzer
,
Michael Antia
,
Jonathan L. Case
, and
Christopher R. Hain

Abstract

Twenty-six years of lightning data were paired with over 68 000 lightning-initiated wildfire (LIW) reports to understand lightning flash characteristics responsible for ignition in between 1995 and 2020. Results indicate that 92% of LIW were started by negative cloud-to-ground (CG) lightning flashes and 57% were single stroke flashes. Moreover, 62% of LIW reports did not have a positive CG within 10 km of the start location, contrary to the science literature’s suggestion that positive CG flashes are a dominant fire-starting mechanism. Nearly ⅓ of wildfire events were holdovers, meaning 1 or more days elapsed between lightning occurrence and fire report. However, fires that were reported less than a day after lightning occurrence statistically burned more acreage. Peak current was not found to be a statistically significant delineator between fire starters and non–fire starters for negative CGs but was for positive CGs. Results highlighted the need for reassessing the role of positive CG lightning and subsequently long-continuing current in wildfire ignition started by lightning. One potential outcome of this study’s results is the development of real-time tools to identify ignition potential during lightning events to aid in fire mitigation efforts.

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