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Daniel Whitesel
,
Rezaul Mahmood
,
Christopher Phillips
,
Joshua Roundy
,
Eric Rappin
,
Paul Flanagan
,
Joseph A. Santanello Jr.
,
Udaysankar Nair
, and
Roger Pielke Sr.

Abstract

Land-use land-cover change affects weather and climate. This paper quantifies land–atmosphere interactions over irrigated and nonirrigated land uses during the Great Plains Irrigation Experiment (GRAINEX). Three coupling metrics were used to quantify land–atmosphere interactions as they relate to convection. They include the convective triggering potential (CTP), the low-level humidity index (HIlow), and the lifting condensation level (LCL) deficit. These metrics were calculated from the rawinsonde data obtained from the Integrated Sounding Systems (ISSs) for Rogers Farm and York Airport along with soundings launched from the three Doppler on Wheels (DOW) sites. Each metric was categorized by intensive observation period (IOP), cloud cover, and time of day. Results show that with higher CTP, lower HIlow, and lower LCL deficit, conditions were more favorable for convective development over irrigated land use. When metrics were grouped and analyzed by IOP, compared to nonirrigated land use, HIlow was found to be lower for irrigated land use, suggesting favorable conditions for convective development. Furthermore, when metrics were grouped and analyzed by clear and nonclear days, CTP values were higher over irrigated cropland than nonirrigated land use. In addition, compared to nonirrigated land use, the LCL deficit during the peak growing season was lower over irrigated land use, suggesting a favorable condition for convection. It is found that with the transition from the early summer to the mid/peak summer and increased irrigation, the environment became more favorable for convective development over irrigated land use. Finally, it was found that regardless of background atmospheric conditions, irrigated land use provided a favorable environment for convective development.

Restricted access
Junkai Qian
,
Qiang Wang
,
Peng Liang
,
Suqi Peng
,
Huizan Wang
, and
Yanling Wu

Abstract

The Kuroshio intrusion (KI) into the South China Sea (SCS) significantly affects the environment, ecology, and climate change of the SCS. However, due to the nonlinearity of KI, its numerical prediction often requires a large ensemble size to measure prediction uncertainty. The huge computational costs of large numbers of members and high-resolution numerical models pose significant challenges for KI prediction. We, therefore, construct a Kuroshio ensemble deep learning prediction system (KurNet) by taking different values of parameters to predict KI paths because the deep learning models have high prediction skills and low computational cost. The KurNet containing 64 ensemble members not only can output ensemble mean forecast results of the Kuroshio path but also can estimate probability density functions for the path types. The KurNet illustrates a high predictive ability for the KI with the mean classification accuracy of 71.9% and root-mean-square error of 0.913 on the testing set, which is superior to the single control prediction by ∼1.0%–2.9%, although the control prediction model is selected as one of the ensemble members with the best predictive ability on the validation set. Furthermore, the predictability analysis of 10 KI events indicates that when the lead time is 3 days, the most important areas are in the east of Luzon Island due to the upstream Kuroshio transport. As the lead time increases, the most important area is in the Luzon Strait due to the eddy activity. Observing system simulation experiments reveal that the KI forecast skill can be enhanced by ∼12%–18% when uncertainties of the input data in these important regions are removed.

Restricted access
Dongxue Mo
,
Po Hu
,
Jian Li
,
Yijun Hou
, and
Shuiqing Li

Abstract

The wave effect is crucial to coastal ocean dynamics, but the roles of the associated wave-dependent mechanisms, such as the wave-enhanced surface stress, wave-enhanced bottom stress, and three-dimensional wave force, are not yet fully understood. In addition, the parameterizations of each mechanism vary and need to be assessed. In this study, a coupled wave–current model based on the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) model system was established to identify the effect of the wave-dependent mechanism on storm surges and currents during three typical extreme weather systems, i.e., cold wave, extratropical cyclone, and typhoon systems, in a semienclosed sea. The effects of the three coupled mechanisms on the surface or bottom stress, in terms of both magnitude and direction, were investigated and quantified separately based on numerical sensitivity analysis. A total of seven parameterizations is used to evaluate these mechanisms, resulting in significant variations in the storm surge and current vectors. The similarities and differences of the wave-induced surge and wave-induced current among the various mechanisms were summarized. The change in the surface stress and bottom stress and the excessive momentum flux due to waves were found to mainly occur in shallow nearshore regions. Optimal choice of the combination of parameterization schemes was obtained through comparison with measured data. The wave-induced current in the open waters with a deep-water depth and complex terrain could generate cyclonic or anticyclonic current vorticities, the number and intensity of which always increased with the enhanced strength and rotation of the wind field increased.

Significance Statement

Waves induced by extreme weather systems can significantly modulate the storm surge and current field. Previous studies have developed different parameterizations for each physical mechanism. In this study, we aimed to separate and quantify the contribution of the wave-dependent mechanisms with typical parameterizations for storm surges and currents during three types of weather systems. The prediction of wave-induced surges in nearshore regions is critical especially during extreme weather systems and has diverse practical applications in ocean engineering. Through comparison with measured data, the best combination of parameterizations was identified, which could be helpful for regional disaster warning and management.

Restricted access
J. Anselin
,
P. R. Holland
,
A. Jenkins
, and
J. R. Taylor

Abstract

Efforts to parameterize ice shelf basal melting within climate models are limited by an incomplete understanding of the influence of ice base slope on the turbulent ice shelf–ocean boundary current (ISOBC). Here, we examine the relationship between ice base slope, boundary current dynamics, and melt rate using 3D, turbulence-permitting large-eddy simulations (LESs) of an idealized ice shelf–ocean boundary current forced solely by melt-induced buoyancy. The range of simulated slopes (3%–10%) is appropriate to the grounding zone of small Antarctic ice shelves and to the flanks of relatively wide ice base channels, and the initial conditions are representative of warm-cavity ocean conditions. In line with previous studies, the simulations feature the development of an Ekman boundary layer adjacent to the ice, overlaying a broad pycnocline. The time-averaged flow within the pycnocline is in thermal wind balance, with a mean shear that is only weakly dependent on the ice base slope angle α, resulting in a mean gradient Richardson number 〈Ri g 〉 that decreases approximately linearly with sinα. Combining this inverse relationship with a linear approximation to the density profile, we derive formulations for the friction velocity, thermal forcing, and melt rate in terms of slope angle and total buoyancy input. This theory predicts that melt rate varies like the square root of slope, which is consistent with the LES results and differs from a previously proposed linear trend. The derived scalings provide a potential framework for incorporating slope dependence into parameterizations of mixing and melting at the base of ice shelves.

Significance Statement

The majority of Antarctica’s contribution to sea level rise can be attributed to changes in ocean-driven melting at the base of ice shelves (the floating extensions of the Antarctic ice sheet). Turbulent ocean currents and melting are strongest where the ice base is steeply sloped, but few studies have systematically examined this effect. We use an idealized ice shelf–ocean model to examine how variations in ice base slope influence ocean mixing and ice melting. We derive a formula predicting that melting varies like the square root of the ice base slope, and this scaling is supported by the simulations. These results provide a potential framework for improving the representation of ice shelf melting in climate models.

Open access
Florence L. Beaudry
,
Stéphane Bélair
,
Julie M. Thériault
,
Dikra Khedhaouiria
,
Franck Lespinas
,
Daniel Michelson
,
Pei-Ning Feng
, and
Catherine Aubry

Abstract

The Canadian Precipitation Analysis (CaPA) system provides near-real-time precipitation analyses over Canada by combining observations with short-term numerical weather prediction forecasts. CaPA’s snowfall estimates suffer from the lack of accurate solid precipitation measurements to correct the first-guess estimate. Weather radars have the potential to add precipitation measurements to CaPA in all seasons but are not assimilated in winter due to radar snowfall estimate imprecision and lack of precipitation gauges for calibration. The main objective of this study is to assess the impact of assimilating Canadian dual-polarized radar-based snowfall data in CaPA to improve precipitation estimates. Two sets of experiments were conducted to evaluate the impact of including radar snowfall retrievals, one set using the high-resolution CaPA (HRDPA) with the currently operational quality control configuration and another increasing the number of assimilated surface observations by relaxing quality control. Experiments spanned two winter seasons (2021 and 2022) in central Canada, covering part of the entire CaPA domain. The results showed that the assimilation of radar-based snowfall data improved CaPA’s precipitation estimates 81.75% of the time for 0.5-mm precipitation thresholds. An increase in the probability of detection together with a decrease in the false alarm ratio suggested an improvement of the precipitation spatial distribution and estimation accuracy. Additionally, the results showed improvements for both precipitation mass and frequency biases for low precipitation amounts. For larger thresholds, the frequency bias was degraded. The results also indicated that the assimilation of dual-polarization radar data is beneficial for the two CaPA configurations tested in this study.

Open access
Yu Du
,
Richard Rotunno
,
Zijian Chen
, and
Hongpei Yang

Abstract

This study presents a simple 2D linear analytical model aimed at investigating gravity waves forced by temporally periodic convection near a coastline. This investigation encompasses two distinct convective heating scenarios: deep convective heating and stratiform heating/cooling. Our model explores the intricate behavior of gravity waves in proximity to a time-dependent convective source and examines their propagation characteristics across diverse atmospheric conditions. Close to the convective source, gravity waves demonstrate nearly horizontal propagation with vertically aligned phase lines. The velocity of their propagation primarily depends on the vertical scale of the convective heating. The presence of a tropopause further extends their horizontal reach through partial wave ducting between the surface and the tropopause. However, the horizontal scale of the convective heating also plays a crucial role in determining the horizontal wavelength and, consequently, affecting the horizontal propagation speed of the gravity waves. If the heating horizontal scale is small compared to the horizontal scale of free waves at the forcing frequency, the heating vertical scale determines the vertical wavelength and thus the horizontal wavelength. However, if the heating horizontal scale is large, the horizontal wavelength determined by the heating vertical scale has little energy, so that the horizontal wavelength is mainly determined by the heating horizontal scale. Moreover, longer periods of convective heating and stronger background winds contribute to an increased downstream propagation distance of the gravity waves away from the source. Additionally, inertia–gravity waves generated by diurnal convection can propagate horizontally over greater distances at a higher latitude but become confined or trapped at latitudes exceeding 30°.

Restricted access
Hongyuan Zhao
,
Jianping Li
,
Yuan Liu
,
Emerson Delarme
, and
Ning Wang

Abstract

The North Atlantic Ocean forcings are considered an important origin of the North Atlantic atmospheric multidecadal variability. Here we reveal the energetics mechanisms of the phenomenon using the perturbation potential energy (PPE) theory. Supporting the previous model studies, a cyclic pattern involving the Atlantic multidecadal oscillation (AMO) and North Atlantic tripole (NAT) is observed: positive AMO phase (AMO+, similarly hereafter) →NAT→AMO→NAT+, with a phase lag of approximately 15~20 years. An atmospheric mode characterized by basin-scale sea level pressure anomaly in the North Atlantic is associated with the AMO, which is termed the North Atlantic uniformity (NAU). The AMO+ induces positive uniform PPE anomalies over the ocean through precipitation heating, leading to decreased energy conversion to perturbation kinetic energy (PKE) and a large-scale anomalous cyclone. For the NAT+, tripolar precipitation anomalies result in tripolar PPE anomalies. Anomalous energy conversions occur where the PPE anomaly gradient is large, explained by an energy balance derived from thermal wind relationship. The PKE around 15°N and 50°N (25°N and 75°N) increases (decreases), forming the anomalous anticyclone and cyclone at subtropical and subpolar region, respectively, known as the North Atlantic Oscillation (NAO). The reverse holds for the NAT and AMO. As the phases of the ocean modes alternate, the energetics induce the NAU, NAO, NAU+, and NAO+ sequentially. In the multidecadal cycle, the accumulated energetics process is related to delayed effect, and the difference in variance explanation between the NAU and NAO is attributed to the feedback mechanisms.

Restricted access
Hongping Gu
,
Wei Zhang
, and
Robert Gillies

Abstract

The Great Salt Lake (GSL) is a shallow terminal lake located in northern Utah, United States. Over the years, the water extent of the GSL has undergone substantial reduction due to water diversions and a changing climate—in particular rising temperatures. However, the potential impacts of the shrinking GSL water body on the local hydroclimate system are poorly understood. In this study, we utilized the Weather Research and Forecasting Model, version 4.2, coupled with a lake model to simulate a series of high-resolution numerical experiments; these experiments aimed to assess the effect of varying lake areal extents on a storm event that occurred on 6 June 2007. The results revealed a systematic decline in the quantity of precipitation over the GSL and downwind regions with declining areal coverage. In the event of complete disappearance, the regional average precipitation would experience an approximate 50% reduction relative to its 2004 base lake extent; this decrease is principally attributed to a diminished water vapor flux and moist static energy (MSE) above the lake. The research underscores the consequences of a shrinking GSL, not just for precipitation delivery downstream but that of a negative feedback loop within the hydroclimatic system of the GSL basin, i.e., water flow reductions into the basin.

Restricted access
Wilbert Weijer
,
Milena Veneziani
,
Jaclyn Clement Kinney
,
Wieslaw Maslowski
,
Jiaxu Zhang
, and
Michael Steele
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
,
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 rain forest photosynthesis and turbulent fluxes influenced by clouds? To what extent are clouds affected by local processes driven by rain forest energy, water, and carbon fluxes? These interrelated questions were the main drivers of the intensive field experiment CloudRoots-Amazon22 which took place at the Amazon Tall Tower Observatory (ATTO)/Campina supersites in the Amazon rain forest 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 subdiurnal 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-min 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 for a 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 rain forest.

Open access