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Kaighin A. McColl
and
Lois I. Tang

Abstract

There is no simple explanation for the spatial structure of near-surface relative humidity over land. We present a diagnostic theory for zonally and temporally averaged near-surface relative humidity (RH) over land based on energy budgets of an atmospheric column in radiative–convective equilibrium. The theory analytically relates RH to the surface evaporative fraction (EF), has no calibrated parameters, and is quantitatively accurate when compared with RH from a reanalysis, and with cloud-permitting simulations over an idealized land surface. The theory is used to answer two basic questions. First, why is RH never especially low (e.g., 1%)? The theory shows that established lower bounds on EF over land and ocean are equivalent to lower bounds on RH that preclude particularly low values, at least for conditions typical of the modern Earth. Second, why is the latitudinal profile of RH over land shaped like the letter W, when both specific humidity and saturation specific humidity essentially decline monotonically from the equator to the poles? The theory predicts that the latitudinal profile of RH should look more like that of water stored in the soil (which also exhibits a W-shaped profile) than in the air (which does not).

Open access
David Cannon
,
Jia Wang
,
Ayumi Fujisaki-Manome
,
James Kessler
,
Steve Ruberg
, and
Steve Constant

Abstract

While changing lake surface conditions have received significant research scrutiny, changes in subsurface conditions, including stratification and heat content, remain largely unexplored. In this work, we highlight changes in thermal structure, stratification dynamics, and ice characteristics in the Laurentian Great Lakes (Lakes Superior, Huron, Michigan, Erie, and Ontario) as simulated between 1979 and 2021. Three-dimensional lake hydrodynamics and ice cover were modeled using the Finite Volume Community Ocean Model (FVCOM) coupled with the Los Alamos sea ice model (CICE). Analysis revealed significant increases in surface (0.4°–0.6°C decade−1) and subsurface (0.1°–0.4°C decade−1) temperatures as well as dramatic losses in ice cover (1%–8% decade−1) and ice volume (0–3 km3 decade−1) over the last 40 years. Estimated surface heating rates were strongest during the summer and fall, while subsurface warming was most rapid during the nearly isothermal winter and spring. Intensified (decreased) summer (winter) stratification led to shifts in lake turnover dynamics, with delayed fall turnover dates (2–6 days decade−1) and earlier spring overturn dates (2–9 days decade−1). Modeled surface temperatures (LST), bottom temperatures (LBT), and annual averaged ice cover (AAIC) were used to estimate low-frequency climate signals, which were highly correlated with the Atlantic multidecadal oscillation. Warming trends fit to residual climate signals (LST: 0.1°C decade−1; LBT: 0.03°C decade−1; AAIC: −1% decade−1), calculated by removing low-frequency variability from the raw climate signal, were lower than those fit to associated low-frequency components, suggesting that recent climate change in the Great Lakes may be strongly influenced by natural multidecadal climate variability.

Restricted access
Anja Katzenberger
,
Stefan Petri
,
Georg Feulner
, and
Anders Levermann

Abstract

Monsoon systems transport water and energy across the globe, making them a central component of the global circulation system. Changes in different forcing parameters have the potential to fundamentally change the monsoon characteristics as indicated in various paleoclimatic records. Here, we use the Atmosphere Model developed at the Geophysical Fluid Dynamics Laboratory (GFDL-AM2) and couple it with a slab ocean in order to analyze the monsoon’s sensitivity to changes in different parameters on a planet with idealized topography (varying land position, slab depth, atmospheric CO2 concentration, solar radiation, sulfate aerosol concentration, and surface albedo). This Monsoon Planet concept of an aquaplanet with a broad zonal land stripe allows us to reduce the influence of topography and to access the relevant meridional monsoon dynamics. In simulations with monsoon dynamics, a bimodal rainfall distribution develops during the monsoon months with one maximum over the tropical ocean and the other one over land. The intensity and extent of the monsoon depend on the relative height of a local maximum in the surface pressure field that is acting as a barrier and is determining the coastward moisture transport. Changes in the barrier height occur during the course of one year but can also be induced when varying different parameters in the sensitivity analysis (e.g., the increase of atmospheric CO2 reduces the barrier height, resulting in an increase of rainfall, while aerosols have the opposing effect). This bimodal rainfall structure separated by a pressure barrier is also present in reanalysis data of the West African monsoon.

Significance Statement

Monsoon rainfall directly impacts the livelihood of millions of individuals in the tropics. Because monsoons transport energy and water around the globe, their influence reaches far beyond the tropics, and changes in their dynamics affect the climate both locally and globally. The individual monsoon systems are subject to various forcing factors that determine the monsoon characteristics in partly opposing ways. Here, we implement a model setup of the Monsoon Planet to study the monsoon’s sensitivity to various forcings in a simplified design, allowing us to gain new insights into monsoon dynamics. We find that a local maximum in the pressure field is acting as a barrier for moisture transport and thus determines the monsoon characteristics over land.

Restricted access
Wei-Ting Hsiao
,
Eric D. Maloney
,
Nicolas M. Leitmann-Niimi
, and
Christian D. Kummerow

Abstract

Organized deep convective activity has been routinely monitored by satellite precipitation radar from the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM). Organized deep convective activity is found to increase not only with sea surface temperature (SST) above 27°C, but also with low-level wind shear. Precipitation shows a similar increasing relationship with both SST and low-level wind shear, except for the highest low-level wind shear. These observations suggest that the threshold for organized deep convection and precipitation in the tropics should consider not only SST, but also vertical wind shear. The longwave cloud radiative feedback, measured as the tropospheric longwave cloud radiative heating per amount of precipitation, is found to generally increase with stronger organized deep convective activity as SST and low-level wind shear increase. Organized deep convective activity, the longwave cloud radiative feedback, and cirrus ice cloud cover per amount of precipitation also appear to be controlled more strongly by SST than by the deviation of SST from its tropical mean. This study hints at the importance of non-thermodynamic factors such as vertical wind shear for impacting tropical convective structure, cloud properties, and associated radiative energy budget of the tropics.

Significance Statement

This study uses tropical satellite observations to demonstrate that vertical wind shear affects the relationship between sea surface temperature and tropical organized deep convection and precipitation. Shear also affects associated cloud properties and how clouds affect the flow of radiation in the atmosphere. Although how vertical wind shear affects convective organization has long been studied in the mesoscale community, the study attempts to apply mesoscale theory to explain the large-scale mean organization of tropical deep convection, cloud properties, and radiative feedbacks. The study also provides a quantitative observational baseline of how vertical wind shear modifies cloud radiative effects and convective organization, which can be compared to numerical simulations.

Restricted access
Yi Peng
,
Yi-Peng Guo
,
Jiuwei Zhao
,
Zhe-Min Tan
,
Xu Chen
, and
Xiangbo Feng

Abstract

Current coupled climate models contain large biases in simulating tropical cyclogenesis, reducing the confidence in tropical cyclone (TC) projection. In this study, we investigated the influence of sea surface temperature (SST) biases on TC genesis in the Coupled Model Intercomparison Project phase 6 simulations from 1979 to 2014. Positive TC genesis biases were found over the tropical central North Pacific (CNP) in most of climate models, including the high-resolution models. Compared to coupled models, TC genesis density (TCGD) simulations over CNP in uncoupled models forced by observational SST improved obviously. A warm SST bias over the tropical CNP in the coupled models is the main cause of TC genesis biases. The SST bias–induced diabatic heating leads to an anomalous Gill-type atmospheric circulation response, which contributes to a series of favorable environmental conditions for TC formation over the CNP. Numerical experiments were also performed with HiRAM to demonstrate the influence of SST biases on the TCGD simulation, further confirming our conclusion. The current results highlight the importance of improving TC simulation in state-of-the-art climate models by reducing SST simulation bias.

Restricted access
Chenhui Jin
,
Michael J. Reeder
,
Ailie J. E. Gallant
,
Tess Parker
, and
Michael Sprenger

Abstract

This study focuses on the rainfall-producing weather systems in the southern Murray–Darling Basin (MDB), Australia. These weather systems are divided into objects: cyclones, fronts, anticyclones, warm conveyor belt (WCB) inflows, WCB ascents, potential vorticity (PV) streamers, and cutoff lows. We investigate the changes in the frequency, amplitude, and relative position of these objects as the daily and seasonal rainfall change. Days on which the rainfall is heavy, especially in winter, are characterized by more PV streamers, cutoff lows, cyclones, fronts, and WCBs in the region. In contrast, dry days are characterized by more anticyclones over southeastern Australia in winter and summer. The effect of upper-level weather objects (PV streamers and cutoff lows) on lower-level objects, and their importance in producing rainfall, is quantified using the quasigeostrophic ω equation and separating the vertical motion into that induced by the upper and lower levels. On heavy rainfall days in winter, PV streamers and cutoff lows force strong upward motion in the lower troposphere, promoting cyclogenesis at lower levels, forcing ascent in the WCBs, and producing rain downstream of the southern MDB. Lower-level ascent forced by upper-level objects is important for the development of heavy rainfall in both seasons, although particularly in winter. Rainfall is attributed to individual objects. PV streamers and WCBs contribute most to the winter and summer rainfall, respectively. The difference in rainfall between anomalously wet and dry years can be explained in winter by the changes in the rainfall associated with PV streamers, whereas in summer it is mostly due to a reduction in the rainfall associated with WCBs.

Significance Statement

The aim of the present study is to better understand how synoptic-scale weather systems differ in southeastern Australia in dry and wet periods, by considering a wide range of weather systems. We found weather systems are more closely aligned in the vertical on heavy rainfall days, and the majority of rainfall in this region is associated with warm conveyor belts. These results point to warm conveyor belts being an important, but not well recognized, contributor to rainfall in this region. Future work may investigate the roles of the various modes of variability and climate change in modulating warm conveyor belts and hence the regional rainfall variability in Australia.

Restricted access
Kexing Yu
and
Kaicun Wang

Abstract

The surface and air temperature gradient (T S00T air) drives the development of the convective boundary layer and the occurrence of clouds and precipitation. However, its variability is still poorly understood due to the lack of high-quality observations. This study fills in this gap by investigating the diurnal to decadal variability in T S00T air from 2002 to 2022 based on hourly observations collected at over 100 stations of the U.S. Climate Reference Network. It is found that T S00T air reaches its maximum at noon with an average of 6.85°C over the contiguous United States, which decreases to 4.28°C when the soil moisture exceeds 30%. The daily minimum of T S00T air has an average of −2.08°C, which generally occurs in the early evening but is postponed as the cloud fraction decreases. Moreover, while existing studies have used the near-surface soil temperature, such as the 5-cm soil temperature (T S05), to calculate T S05T air, we find that T S00T air and T S05T air have opposite diurnal cycles, and their amplitudes differed drastically. The daily minimum of T S00T air has a significant decreasing trend (−0.50° ± 0.007°C decade−1) from 2002 to 2022 due to T air increasing at a higher rate than T S00 during the nighttime. The occurrence frequency of near-surface stable conditions (T S00T air < 0) increases significantly, and the frequency of unstable conditions (T S00T air > 0) decreases notably throughout the year except for winter. When it is stable, the magnitude of T S00T air tends to decrease while the T S00T air tends to increase when it is unstable, which is consistent with the drying condition caused by the precipitation deficit. This study provides the first observational evidence on how T S00T air responds to warming.

Significance Statement

The impact of global warming on surface-air temperature gradients is a crucial scientific issue that needs to be addressed. These gradients determine changes in cloud and precipitation, affecting water resources. However, traditional surface temperature measurements from weather stations are of high uncertainty due to direct exposure to the insolation. Satellite retrieval of surface temperature is limited by the availability of clear sky conditions, with low accuracy for temperature gradient calculations. Despite their importance, high-accuracy data of land surface temperature are still lacking. To address this issue, the U.S. Climate Reference Network (USCRN) uses infrared radiometers to continuously monitor surface temperature with high accuracy and sampling frequency. This study reports on surface-air temperature gradients at more than 100 U.S. stations, providing insight into diurnal to decadal variability over the contiguous United States. The study also highlights the significant difference between the land surface temperature–air temperature gradient and soil temperature–air temperature gradient.

Restricted access
Kjersti Konstali
,
Clemens Spensberger
,
Thomas Spengler
, and
Asgeir Sorteberg

Abstract

Weather features, such as extratropical cyclones (ETCs), atmospheric rivers (ARs), and fronts, contribute to substantial amounts of precipitation globally. However, previous estimates of how much these individual features contribute to precipitation are very sensitive to subjectively chosen metrics. Furthermore, there is no information on how these weather features contribute to precipitation poleward of 60° latitude. To alleviate these shortcomings, we introduce a more robust attribution method applicable at all latitudes. Based on ERA5, we present the first global climatology of the contributions from cyclones, fronts, moisture transport axes (MTAs; AR-like features), and cold air outbreaks, as well as their combinations, to summer and winter precipitation as well as extreme precipitation. Most of the precipitation in the midlatitudes relates to the combination of ETC, fronts, and MTAs (28%), while in polar regions most precipitation occurs within the ETC-only category (27%). Extreme precipitation events in all extratropical regions are predominantly associated with the combination of ETCs, fronts, and MTAs (46%). In the midlatitudes, the combination of ETCs, fronts, and MTAs occurs almost 4 times as often during extreme events compared to regular events.

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Michelle L. L’Heureux
,
Michael K. Tippett
,
Matthew C. Wheeler
,
Hanh Nguyen
,
Sugata Narsey
,
Nathaniel Johnson
,
Zeng-Zhen Hu
,
Andrew B. Watkins
,
Chris Lucas
,
Catherine Ganter
,
Emily Becker
,
Wanqiu Wang
, and
Tom Di Liberto

Abstract

El Niño–Southern Oscillation (ENSO) is often characterized through the use of sea surface temperature (SST) departures from their climatological values, as in the Niño-3.4 index. However, this approach is problematic in a changing climate when the climatology itself is varying. To address this issue, van Oldenborgh et al. proposed a relative Niño-3.4 SST index, which subtracts the tropical mean SST anomaly from the Niño-3.4 index and multiplies by a scaling factor. We extend their work by providing a simplified calculation procedure for the scaling factor, and confirm that the relative index demonstrates reduced sensitivity to climate change and multidecadal variability. In particular, we show in three observational SST datasets that the relative index provides a more consistent classification of historical El Niño and La Niña oceanic conditions that is more robust across climatological periods compared to the nonrelative index. Forecast skill of the relative Niño-3.4 index in the North American Multimodel Ensemble (NMME) and ACCESS-S2 is slightly reduced for targets during the first half of the year because subtracting the tropical mean removes a source of additional skill. For targets in the second half of the year, the relative and nonrelative indices are equally skillful. Observed ENSO teleconnections in 200-hPa geopotential height and precipitation during key seasons are sharper and explain more variability over Australia and the contiguous United States when computed with the relative index. Overall, the relative Niño-3.4 index provides a more robust option for real-time monitoring and forecasting ENSO in a changing climate.

Significance Statement

The goal of this study is to further explore a relative sea surface temperature index for monitoring and prediction of El Niño–Southern Oscillation. Sea surface temperature indices are typically computed as a difference from a 30-yr climatological average, and El Niño and La Niña events occur when values exceed a certain threshold. This method is suitable when the climate is stationary. However, because of climate change and other lower-frequency variations, historical El Niño and La Niña events are reclassified depending on which climatological period is selected. A relative index is investigated to ameliorate this problem.

Restricted access
Shuo Li
and
Wei Mei

Abstract

The small sample size of tropical cyclone (TC) genesis in the observations prevents us from fully characterizing its spatiotemporal variations. Here we take advantage of a large ensemble of 60-km-resolution atmospheric simulations to address this issue over the northwest Pacific (NWP) during 1951–2010. The variations in annual TC genesis density are explored separately on interannual and decadal time scales. The interannual variability is dominated by two leading modes. One is characterized by a dipole pattern, and its temporal evolution is closely linked to the developing ENSO. The other mode features high loadings in the central part of the basin, with out-of-phase changes near the equator and date line, and tends to occur during ENSO decay years. On decadal time scales, TC genesis density variability is primarily controlled by one mode, which exhibits an east–west dipole pattern with strong signals confined to south of 20°N and is tied to the interdecadal Pacific oscillation–like sea surface temperature anomalies. Further, we investigate the seasonal evolution of the ENSO effect on TC genesis density. The results highlight the distinct impacts of the two types of ENSO (i.e., eastern Pacific vs central Pacific) on TC genesis density in the NWP during a specific season and show the strong seasonal dependency of the TC genesis response to ENSO. Although the results from the observations are not as prominent as those from the simulations because of the small sample size, the high consistency between them demonstrates the fidelity of the model in reproducing TC statistics and variability in the observations.

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