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A. R. Siders
and
Dana Veron
Open access
Anda Vladoiu
,
Ren-Chieh Lien
, and
Eric Kunze

Abstract

Shipboard ADCP velocity and towed CTD chain density measurements from the eastern North Pacific pycnocline are used to segregate energy between linear internal waves (IW) and linear vortical motion [quasigeostrophy (QG)] in 2D wavenumber space spanning submesoscale horizontal wavelengths λx ∼ 1–50 km and finescale vertical wavelengths λz ∼ 7–100 m. Helmholtz decomposition and a new Burger number (Bu) decomposition yield similar results despite different methodologies. While these wavelengths are conventionally attributed to internal waves, both QG and IW contribute significantly at all measured scales. Partition between IW and QG total energies depends on Bu. For Bu < 0.01, available potential energy EP exceeds horizontal kinetic energy EK and is contributed mostly by QG. In contrast, energy is nearly equipartitioned between QG and IW for Bu ≫ 1. For Bu < 2, EK is contributed mainly by IW, and EP by QG, while, for Bu > 2, contributions are reversed. Finescale near-inertial IW dominate vertical shear variance, implying negligible QG contribution to vertical shear instability. In contrast, both QG and IW at the smallest λx ∼ 1 km contribute large horizontal shear variance, so that both may lead to horizontal shear instability, while QG, with its longer time scales, likely dominates isopycnal stirring. Both QG and IW contribute to vortex stretching at small vertical scales. For QG, the relative vorticity contribution to linear potential vorticity anomaly increases with decreasing horizontal and increasing vertical scales.

Open access
Pei-Syuan Liao
,
Chia-Wei Lan
,
Yu-Chiao Liang
, and
Min-Hui Lo

Abstract

The annual range (AR) of precipitation in the Amazon River basin has increased steadily since 1979. This increase may have resulted from natural variability and/or anthropogenic forcing, such as local land-use changes and global warming, which has yet to be explored. In this study, climate model experiments using the Community Earth System Model, version 2 (CESM2), were conducted to examine the relative contributions of sea surface temperatures (SSTs) variability and anthropogenic forcings to the AR changes in the Amazon rainfall. With CESM2, we design several factorial simulations, instead of actual model projection. We found that the North Atlantic SSTs fluctuation dominantly decreases the precipitation AR trend over the Amazon by −85%. In contrast, other factors, including deforestation and carbon dioxide, contributed to the trend changes, ranging from 25% to 35%. The dynamic component, specifically the tendency of vertical motion, made negative contributions, along with the vertical profiles of moist static energy (MSE) tendency. Seasonal-dependent changes in atmospheric stability could be associated with variations in precipitation. It is concluded that surface ocean warming associated with the North Atlantic natural variability and global warming is the key factor in the increased precipitation AR over the Amazon from 1979 to 2014. The continuous local land-use changes may potentially influence the precipitation AR in the future.

Significance Statement

The annual range (AR) in precipitation, the difference between wet- and dry-season precipitation, has increased from 1979 to 2014 in the Amazon. This increase may have resulted from global warming, deforestation, and sea surface temperature variability in North Atlantic and Pacific. To explore the role of each of these factors in altering the Amazon precipitation AR, five experiments were designed in the climate model (CESM). Among these experiment results, the effect of North Atlantic SSTs was the strongest. In the future, deforestation, global warming, and different ocean temperature states in the North Atlantic and Pacific may become increasingly influential on the changes in precipitation. Further investigation is needed to ascertain how the AR of precipitation in the Amazon will change.

Restricted access
Kouya Nakamura
,
Shoichiro Kido
,
Takashi Ijichi
, and
Tomoki Tozuka

Abstract

The mean vertical advection of anomalous vertical temperature gradient is considered the dominant generation mechanism of positive sea surface temperature (SST) anomalies associated with the canonical El Niño. However, most past studies had a residual term in their heat budget analysis and/or did not quantify the role of vertical mixing even though active vertical turbulent mixing in the upper ocean is observed in the eastern equatorial Pacific. To quantitatively assess the importance of vertical mixing, a mixed layer heat budget analysis is performed using a hindcast simulation forced by daily mean atmospheric reanalysis data. It is found that when the mixed layer depth is defined as the depth at which potential density increases by 0.125 kg m−3 from the sea surface, the development of positive SST anomalies is predominantly governed by reductions in the cooling by vertical mixing, and their magnitude is much larger than those by vertical advection. The anomalous warming by vertical mixing may be partly explained by an anomalous deepening of the thermocline that leads to a decrease in the vertical temperature gradient, giving rise to suppression of the climatological cooling by vertical mixing. Also, an anomalously thick mixed layer reduces sensitivity to cooling by the mean vertical mixing and contributes to the anomalous SST warming. On the other hand, the dominant negative feedbacks are attributed to both anomalous surface heat loss and anomalous deepening of the mixed layer that weakens warming by the mean surface heat flux.

Restricted access
Russell C. Schnell
and
Gabor Vali

Abstract

In Part I, we described the discoveries we and our associates made in the 1960s and 1970s about biological ice nucleating particles (bio-INPs). The bio-INPs are far more effective than mineral INPs at temperatures above −10°C. The bio-INPs were found in decayed vegetation and in ocean water, and then, bacteria were identified as being the most active source for this remarkable activity. In this Part II, we recount how, within a few years, the worldwide distribution of bio-INP sources was shown to correlate with climate zones, as was the abundance of INPs in precipitation. Oceanic sources were further studied, and the presence of bio-INPs in fog diagnosed. The potential for release of bio-INPs from the ground to the atmosphere was demonstrated. Bacterial INPs were found to play a crucial role in a plant’s frost resistance. These and other early developments of biological INPs are described. A bibliography of related recent literature is presented in the online supplemental material (https://doi.org/10.1175/BAMS-D-23-0114.s1).

Open access
Belinda Trotta

Abstract

Ensemble Copula Coupling (Schefzik et al. 2013) is a widely used method to produce a calibrated ensemble from a calibrated probabilistic forecast. This process improves the statistical accuracy of the ensemble; in other words, the distribution of the calibrated ensemble members at each grid point more closely approximates the true expected distribution. However, the trade-off is that the individual members are often less physically realistic than the original ensemble: there is noisy variation among neighboring grid points, and, depending on the calibration method, extremes in the original ensemble are sometimes muted. We introduce Neighborhood Ensemble Copula Coupling (N-ECC), a simple modification of ECC designed to mitigate these problems. We show that, when used with the calibrated forecasts produced by Flowerdew’s (Flowerdew 2014) reliability calibration, N-ECC improves both the visual plausibility and the statistical properties of the forecast.

Restricted access
Zili Shen
,
Anmin Duan
,
Wen Zhou
,
Yuzhuo Peng
, and
Jinxiao Li

Abstract

Two large ensemble simulations are adopted to investigate the relative contribution of external forcing and internal variability to Arctic sea ice variability on different time scales since 1960 by correcting the response error of models to external forcing using observational datasets. Our study suggests that previous approaches might overestimate the real impact of internal variability on Arctic sea ice change especially on long time scales. Our results indicate that in both March and September, internal variability plays a dominant role on all time scales over the twentieth century, while the anthropogenic signal on sea ice change can be steadily and consistently detected on a time scale of more than 20 years after the 2000s. We also reveal that the dominant mode of internal variability in March shows consistency across different time scales. On the contrary, the pattern of internal variability in September is highly nonuniform over the Arctic and varies across different time scales, indicating that sea ice internal variability in September at different time scales is driven by different factors.

Open access
Christopher P. McKay
and
Mateo N. Cintron

Abstract

The thermal equator (also known as the heat equator) is the circumplanetary set of points that represent the highest mean annual temperature at each longitude. Recent high precision global datasets for Earth and Mars provide a basis for a detailed calculation of the thermal equator on these worlds. On Earth, the temperature values that comprise the thermal equator range from 25.85° to 34.75°C, with a mean of 27.75° ± 1.3°C, and extends in latitude as high as 20°N in Mexico and 29.3°N in the Indian subcontinent. The maximum southern extent is 20°S in Australia. On Mars, lacking oceans, the thermal equator takes a simpler track and is roughly parallel to the equator, and displaced 5°–10°S. However, there is a region of longitude on Mars where the thermal equator becomes bimodal with a northern branch centered at 10°N and a southern branch centered at 20°S.

Open access
Hongqing Yang
and
Ke Fan

Abstract

The subseasonal variability of winter air temperature in China during 2021/22 underwent significant changes, showing warm, warm, and cold anomalies during 2–23 December 2021 (P1), 1–27 January 2022 (P2), and 28 January–24 February 2022 (P3). The strong (weak) zonal circulation over East Asia led to positive (negative) surface air temperature anomalies (SATA) during P1 and P2 (P3). The position of the Siberian high affected the distribution of the warmest center of SATA over northeastern and northwestern China in P1 and P2, respectively. Further investigations indicated that intraseasonal components (10–90 days) primarily drove the warm-to-cold transition in China during P2 and P3, contributing to 79.5% of the variance in SATA in winter 2021/22. Strong (weak) East Asian intraseasonal zonal circulations corresponded to positive (negative) meridional wind anomalies over China–Lake Baikal, affecting the guidance of cold air into China during P2 (P3). East Asian circulation alternations from P2 to P3 were associated with a shift in intraseasonal geopotential height anomalies over the North Atlantic region from positive to negative in the mid-to-high troposphere through the propagation of north and south branch wave trains. The reversal of the North Atlantic geopotential height anomalies between P2 and P3 was modulated by intraseasonal higher-latitude SST anomalies over the North Atlantic and the location of intraseasonal stratospheric polar vortex. Furthermore, the intensified south branch wave train from the Indian Peninsula to China in the mid-to-high troposphere was associated with active convection over the tropical western Indian Ocean during P3. These processes could be verified by using the Linear Baroclinic Model.

Restricted access
Laurence Coursol
,
Sylvain Heilliette
, and
Pierre Gauthier

Abstract

With hyperspectral instruments measuring radiation emitted by Earth and its atmosphere in the thermal infrared range in multiple channels, several studies were made to select a subset of channels in order to reduce the number of channels to be used in a data assimilation system. An optimal selection of channels based on the information content depends on several factors related to observation and background error statistics and the assimilation system itself. An optimal channel selection for the Cross-track Infrared Sounder (CrIS) was obtained and then compared to selections made for different NWP systems. For instance, the channel selection of Carminati has 224 channels also present in our optimal selection, which includes 455 channels. However, in terms of analysis error variance, the difference between the two selections is small. Integrated over the whole profile, the relative difference is equal to 15.3% and 4.5% for temperature and humidity, respectively. Also, different observation error covariance matrices were considered to evaluate the impact of this matrix on channel selection. Even though the channels selected optimally were different in terms of which channels were selected for the various R matrices, the results in terms of analysis error are similar.

Significance Statement

Satellites measure radiation from Earth and its atmosphere in the thermal infrared. Those radiance data contain thousands of measurements, called channels, and thus, a selection needs to be done retaining most of the information content since the large number of individual pieces of information is not usable for numerical weather prediction systems. The goal of this paper is to find an optimal selection for the instrument CrIS and to compare this selection with selections made for different numerical weather prediction systems. It was found that even though the channels selected optimally were different in terms of which channels were selected compared to other selections, the results in terms of precision of the analysis are similar and the results in terms of analysis error are similar due to the nature of hyperspectral instruments, which have multiple Jacobians overlapping.

Open access