scholarly journals Understanding the Atmospheric Temperature Adjustment to CO2 Perturbation at the Process Level

2020 ◽  
Vol 33 (3) ◽  
pp. 787-803 ◽  
Author(s):  
Yuwei Wang ◽  
Yi Huang
Keyword(s):  
Large Scale ◽  
Climate Model ◽  
Temperature Response ◽  
Lower Troposphere ◽  
Atmospheric Temperature ◽  
Climate Simulation ◽  
Large Scale Circulation ◽  
Upper Troposphere ◽  
Rapid Adjustment ◽  
Process Level

AbstractClimate model comparisons show that there is considerable uncertainty in the atmospheric temperature response to CO2 perturbation. The uncertainty results from both the rapid adjustment that occurs before SST changes and the slow feedbacks that occur after SST changes. The analysis in this paper focuses on the rapid adjustment. We use a novel method to decompose the temperature change in AMIP-type climate simulation in order to understand the adjustment at the process level. We isolate the effects of different processes, including radiation, convection, and large-scale circulation in the temperature adjustment, through a set of numerical experiments using a hierarchy of climate models. We find that radiative adjustment triggers and largely controls the zonal mean atmospheric temperature response pattern. This pattern is characterized by stratospheric cooling, lower-tropospheric warming, and a warming center near the tropical tropopause. In contrast to conventional views, the warming center near the tropopause is found to be critically dependent on the shortwave absorption of CO2. The dynamical processes largely counteract the effect of the radiative process that increases the vertical temperature gradient in the free troposphere. The effect of local convection is to move atmospheric energy vertically, which cools the lower troposphere and warms the upper troposphere. The adjustment due to large-scale circulation further redistributes energy along the isentropic surfaces across the latitudes, which cools the low-latitude lower troposphere and warms the midlatitude upper troposphere and stratosphere. Our results highlight the importance of the radiative adjustment in the overall adjustment and provide a potential method to understand the spread in the models.

scholarly journals AMSU-A-Only Atmospheric Temperature Data Records from the Lower Troposphere to the Top of the Stratosphere

2014 ◽  
Vol 31 (4) ◽  
pp. 808-825 ◽  
Author(s):  
Wenhui Wang ◽  
Cheng-Zhi Zou
Keyword(s):  
Climate Model ◽  
Incidence Angle ◽  
Lower Troposphere ◽  
Atmospheric Temperature ◽  
Observation Time ◽  
Temperature Data ◽  
Climate Change Research ◽  
Global Mean Temperature ◽  
Microwave Sounding ◽  
Solar Noon

Abstract The Advanced Microwave Sounding Unit-A (AMSU-A, 1998–present) not only continues but surpasses the Microwave Sounding Unit’s (MSU, 1978–2006) capability in atmospheric temperature observation. It provides valuable satellite measurements for higher vertical resolution and long-term climate change research and trend monitoring. This study presented methodologies for generating 11 channels of AMSU-A-only atmospheric temperature data records from the lower troposphere to the top of the stratosphere. The recalibrated AMSU-A level 1c radiances recently developed by the Center for Satellite Applications and Research group were used. The recalibrated radiances were adjusted to a consistent sensor incidence angle (nadir), channel frequencies (prelaunch-specified central frequencies), and observation time (local solar noon time). Radiative transfer simulations were used to correct the sensor incidence angle effect and the National Oceanic and Atmospheric Administration-15 (NOAA-15) channel 6 frequency shift. Multiyear averaged diurnal/semidiurnal anomaly climatologies from climate reanalysis as well as climate model simulations were used to adjust satellite observations to local solar noon time. Adjusted AMSU-A measurements from six satellites were carefully quality controlled and merged to generate 13+ years (1998–2011) of a monthly 2.5° × 2.5° gridded atmospheric temperature data record. Major trend features in the AMSU-A-only atmospheric temperature time series, including global mean temperature trends and spatial trend patterns, were summarized.

scholarly journals An Initiation Process of Tropical Depression-type Disturbances under the Influence of Upper-level Troughs

2021 ◽  
Author(s):  
Yuya Hamaguchi ◽  
Yukari N. Takayabu
Keyword(s):  
Large Scale ◽  
Convective Available Potential Energy ◽  
Three Dimensional ◽  
Lower Troposphere ◽  
Dimensional Structure ◽  
Convective Heating ◽  
Upper Troposphere ◽  
Tropical Depression ◽  
Upper Level ◽  
Extratropical Forcing

AbstractIn this study, the statistical relationship between tropical upper-tropospheric troughs (TUTTs) and the initiation of summertime tropical-depression type disturbances (TDDs) over the western and central North Pacific is investigated. By applying a spatiotemporal filter to the 34-year record of brightness temperature and using JRA-55 reanalysis products, TDD-event initiations are detected and classified as trough-related (TR) or non-trough-related (non-TR). The conventional understanding is that TDDs originate primarily in the lower-troposphere; our results refine this view by revealing that approximately 30% of TDDs in the 10°N-20°N latitude ranges are generated under the influence of TUTTs. Lead-lag composite analysis of both TR- and non-TR-TDDs clarifies that TR-TDDs occur under relatively dry and less convergent large-scale conditions in the lower-troposphere. This result suggests that TR-TDDs can form in a relatively unfavorable low-level environment. The three-dimensional structure of the wave activity flux reveals southward and downward propagation of wave energy in the upper troposphere that converges at the mid-troposphere around the region where TR-TDDs occur, suggesting the existence of extratropical forcing. Further, the role of dynamic forcing associated with the TUTT on the TR-TDD-initiation is analyzed using the quasi-geostrophic omega equation. The result reveals that moistening in the mid-to-upper troposphere takes place in association with the sustained dynamical ascent at the southeast side of the TUTT, which precedes the occurrence of deep convective heating. Along with a higher convective available potential energy due to the destabilizing effect of TUTTs, the moistening in the mid-to-upper troposphere also helps to prepare the environment favorable to TDDs initiation.

Regional Downscaling for Air Quality Assessment

2007 ◽  
Vol 88 (8) ◽  
pp. 1215-1228 ◽  
Author(s):  
William I. Gustafson ◽  
L. Ruby Leung
Keyword(s):  
Boundary Layer ◽  
Air Quality ◽  
Quality Assessment ◽  
Large Scale ◽  
Dynamical Downscaling ◽  
Circulation Model ◽  
The United States ◽  
Climate Simulation ◽  
Large Scale Circulation ◽  
Air Quality Assessment

Assessing future changes in air quality using downscaled climate scenarios is a relatively new application of the dynamical downscaling technique. This article compares and evaluates two downscaled simulations for the United States made using the fifth-generation Pennsylvania State University–NCAR Mesoscale Model with the goal of understanding how errors in the downscaled climate simulations may introduce uncertainty in air quality assessment. The two downscaled simulations were driven by boundary conditions from the NCEP–NCAR global reanalysis and a global climate simulation generated by the Goddard Institute for Space Studies global circulation model, respectively. Comparisons of the model runs are made against the boundary layer and circulation characteristics of the North American Regional Reanalysis, and also against observed precipitation. The relative dependence of different simulated quantities on regional forcing, model parameterizations, and large-scale circulation provides a framework to understand similarities and differences between model simulations. Results show significant improvements in the downscaled diurnal wind patterns, in response to the complex orography, that are important for air quality assessment. Evaluation of downscaled boundary layer depth and winds, precipitation, and large-scale circulation shows larger biases related to model physics and biases in the GCM large-scale conditions. Based on the comparisons, recommendations are made to improve the utility of downscaled scenarios for air quality assessment.

scholarly journals A Fortran-Keras Deep Learning Bridge for Scientific Computing

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Jordan Ott ◽  
Mike Pritchard ◽  
Natalie Best ◽  
Erik Linstead ◽  
Milan Curcic ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Large Scale ◽  
Climate Model ◽  
Emergent Behavior ◽  
Training Dataset ◽  
Climate Simulation ◽  
Network Architectures ◽  
Efficient Computation ◽  
Radiation Physics

Implementing artificial neural networks is commonly achieved via high-level programming languages such as Python and easy-to-use deep learning libraries such as Keras. These software libraries come preloaded with a variety of network architectures, provide autodifferentiation, and support GPUs for fast and efficient computation. As a result, a deep learning practitioner will favor training a neural network model in Python, where these tools are readily available. However, many large-scale scientific computation projects are written in Fortran, making it difficult to integrate with modern deep learning methods. To alleviate this problem, we introduce a software library, the Fortran-Keras Bridge (FKB). This two-way bridge connects environments where deep learning resources are plentiful with those where they are scarce. The paper describes several unique features offered by FKB, such as customizable layers, loss functions, and network ensembles. The paper concludes with a case study that applies FKB to address open questions about the robustness of an experimental approach to global climate simulation, in which subgrid physics are outsourced to deep neural network emulators. In this context, FKB enables a hyperparameter search of one hundred plus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to be transferred and used in Fortran. Such a process allows the model’s emergent behavior to be assessed, i.e., when fit imperfections are coupled to explicit planetary-scale fluid dynamics. The results reveal a previously unrecognized strong relationship between offline validation error and online performance, in which the choice of the optimizer proves unexpectedly critical. This in turn reveals many new neural network architectures that produce considerable improvements in climate model stability including some with reduced error, for an especially challenging training dataset.

scholarly journals The GFDL CM3 Coupled Climate Model: Characteristics of the Ocean and Sea Ice Simulations

2011 ◽  
Vol 24 (13) ◽  
pp. 3520-3544 ◽  
Author(s):  
Stephen M. Griffies ◽  
Michael Winton ◽  
Leo J. Donner ◽  
Larry W. Horowitz ◽  
Stephanie M. Downes ◽  
...  
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Climate Model ◽  
Atmospheric Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Simulation ◽  
Climate Indices ◽  
Geophysical Fluid Dynamics Laboratory ◽  
Coupled Climate Model

Abstract This paper documents time mean simulation characteristics from the ocean and sea ice components in a new coupled climate model developed at the NOAA Geophysical Fluid Dynamics Laboratory (GFDL). The GFDL Climate Model version 3 (CM3) is formulated with effectively the same ocean and sea ice components as the earlier CM2.1 yet with extensive developments made to the atmosphere and land model components. Both CM2.1 and CM3 show stable mean climate indices, such as large-scale circulation and sea surface temperatures (SSTs). There are notable improvements in the CM3 climate simulation relative to CM2.1, including a modified SST bias pattern and reduced biases in the Arctic sea ice cover. The authors anticipate SST differences between CM2.1 and CM3 in lower latitudes through analysis of the atmospheric fluxes at the ocean surface in corresponding Atmospheric Model Intercomparison Project (AMIP) simulations. In contrast, SST changes in the high latitudes are dominated by ocean and sea ice effects absent in AMIP simulations. The ocean interior simulation in CM3 is generally warmer than in CM2.1, which adversely impacts the interior biases.

Transport into the upper troposphere-lower stratosphere over North America

2020 ◽  
Author(s):  
Xinyue Wang ◽  
William Randel ◽  
Yutian Wu
Keyword(s):  
Gulf Of Mexico ◽  
Large Scale ◽  
Lower Stratosphere ◽  
Climate Model ◽  
Deep Convection ◽  
Vertical Diffusion ◽  
Dynamical Mechanism ◽  
Upper Troposphere ◽  
The North ◽  
Budget Analysis

<p>We study fast transport of air from the surface into the North American upper troposphere-lower stratosphere (UTLS) during northern summer with a large ensemble of Boundary Impulse Response (BIR) idealized tracers. Specifically, we implement 90 pulse tracers at the Northern Hemisphere surface and release them during July and August months in the fully coupled Whole Atmosphere Community Climate Model (WACCM) version 5. We focus on the most efficient transport cases above southern U.S. (10°-40°N, 60°-140°W) at 100 hPa with modal ages fall below 10th percentile. We examine transport-related terms, including resolved dynamics computed inside model transport scheme and parameterized processes (vertical diffusion and convective parameterization), to pin down the dominant dynamical mechanism. Our results show during the fastest transport, air parcels enter ULTS directly above the Gulf of Mexico. The budget analysis indicates that strong deep convection over the Gulf of Mexico fast uplift the tracer into 200 hPa, and then is vertically advected into 100 hPa and circulated by the enhanced large-scale anticyclone. </p>

scholarly journals Simulated pre-industrial climate in Bergen Climate Model (version 2): model description and large-scale circulation features

2009 ◽  
Vol 2 (2) ◽  
pp. 197-212 ◽  
Author(s):  
O. H. Otterå ◽  
M. Bentsen ◽  
I. Bethke ◽  
N. G. Kvamstø
Keyword(s):  
Sea Ice ◽  
Observational Data ◽  
Mixed Layer ◽  
Large Scale ◽  
Climate Model ◽  
Ocean Model ◽  
Meridional Overturning Circulation ◽  
Model Description ◽  
Sea Ice Extent ◽  
Large Scale Circulation

Abstract. The Bergen Climate Model (BCM) is a fully-coupled atmosphere-ocean-sea-ice model that provides state-of-the-art computer simulations of the Earth's past, present, and future climate. Here, a pre-industrial multi-century simulation with an updated version of BCM is described and compared to observational data. The model is run without any form of flux adjustments and is stable for several centuries. The simulated climate reproduces the general large-scale circulation in the atmosphere reasonably well, except for a positive bias in the high latitude sea level pressure distribution. Also, by introducing an updated turbulence scheme in the atmosphere model a persistent cold bias has been eliminated. For the ocean part, the model drifts in sea surface temperatures and salinities are considerably reduced compared to earlier versions of BCM. Improved conservation properties in the ocean model have contributed to this. Furthermore, by choosing a reference pressure at 2000 m and including thermobaric effects in the ocean model, a more realistic meridional overturning circulation is simulated in the Atlantic Ocean. The simulated sea-ice extent in the Northern Hemisphere is in general agreement with observational data except for summer where the extent is somewhat underestimated. In the Southern Hemisphere, large negative biases are found in the simulated sea-ice extent. This is partly related to problems with the mixed layer parametrization, causing the mixed layer in the Southern Ocean to be too deep, which in turn makes it hard to maintain a realistic sea-ice cover here. However, despite some problematic issues, the pre-industrial control simulation presented here should still be appropriate for climate change studies requiring multi-century simulations.

scholarly journals The Development and Assessment of a Model-, Grid-, and Basin-Independent Tropical Cyclone Detection Scheme

2013 ◽  
Vol 26 (15) ◽  
pp. 5493-5507 ◽  
Author(s):  
K. J. Tory ◽  
S. S. Chand ◽  
R. A. Dare ◽  
J. L. McBride
Keyword(s):  
Tropical Cyclone ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Vertical Wind Shear ◽  
Lower Troposphere ◽  
Specific Humidity ◽  
Model Data ◽  
Detector Performance ◽  
Detection Scheme

Abstract A novel approach to tropical cyclone (TC) detection in coarse-resolution numerical model data is introduced and assessed. This approach differs from traditional detectors in two main ways. First, it was developed and tuned using 20 yr of ECMWF Interim Re-Analysis (ERA-Interim) data, rather than using climate model data. This ensures that the detector is independent of any climate models to which it will later be applied. Second, only relatively large-scale parameters resolvable in climate models are included, in order to minimize any grid-resolution dependence on parameter thresholds. This approach is taken in an attempt to construct a unified TC detection procedure applicable to all climate models without the need for any further tuning or adjustment. Unlike traditional detectors that seek to identify TCs directly, the authors' method seeks to identify conditions favorable for TC formation. Favorable TC formation regions at the center of closed circulations in the lower troposphere to the midtroposphere are identified using a low-deformation vorticity parameter. Additional relative and specific humidity thresholds are applied to ensure the thermodynamic environment is favorable, and a vertical wind shear threshold is applied to eliminate storms in a destructive shear environment. A further requirement is that thresholds for all parameters must be satisfied for at least 48 h before a TC is deemed to have developed. A thorough assessment of the detector performance is provided. It is demonstrated that the method reproduces realistic TC genesis frequency and spatial distributions in the ERA-Interim data. Application of the detector to four climate models is presented in a companion paper.

scholarly journals Global climate forcing driven by altered BVOC fluxes from 1990–2010 land cover change in maritime Southeast Asia

2018 ◽  
Author(s):  
Kandice L. Harper ◽  
Nadine Unger
Keyword(s):  
Land Cover ◽  
Southeast Asia ◽  
Land Cover Change ◽  
Radiative Forcing ◽  
Large Scale ◽  
Lower Troposphere ◽  
Convective Transport ◽  
Atmospheric Composition ◽  
Land Cover Changes ◽  
Upper Troposphere

Abstract. Over the period 1990–2010, maritime Southeast Asia experienced large-scale land cover changes, including expansion of high-isoprene-emitting oil palm plantations and contraction of low-isoprene-emitting natural forests. The ModelE2-Yale Interactive Terrestrial Biosphere global chemistry–climate model is used to quantify the atmospheric composition changes and, for the first time, the associated radiative forcing induced by the land-cover-change-driven biogenic volatile organic compound (BVOC) emission changes (+6.5 TgC y−1 isoprene, −0.5 TgC y−1 monoterpenes). Regionally, surface-level ozone concentrations largely decreased (−3.8 to +0.8 ppbv). The tropical land cover changes occurred in a region of strong convective transport, providing a mechanism for the BVOC perturbations to affect the composition of the upper troposphere. Enhanced concentrations of isoprene and its degradation products are simulated in the upper troposphere, and, on a global-mean basis, land cover change had a stronger impact on ozone in the upper troposphere (+0.6 ppbv) than in the lower troposphere (

scholarly journals Greenland accumulation and its connection to the large-scale atmospheric circulation in ERA-Interim and paleoclimate simulations

2013 ◽  
Vol 9 (6) ◽  
pp. 2433-2450 ◽  
Author(s):  
N. Merz ◽  
C. C. Raible ◽  
H. Fischer ◽  
V. Varma ◽  
M. Prange ◽  
...  
Keyword(s):  
Atmospheric Circulation ◽  
Large Scale ◽  
Climate Model ◽  
Ice Core ◽  
Ice Cores ◽  
Circulation Pattern ◽  
Large Scale Circulation ◽  
Atmospheric Circulation Patterns ◽  
The Stability ◽  
The Relationship

Abstract. Changes in Greenland accumulation and the stability in the relationship between accumulation variability and large-scale circulation are assessed by performing time-slice simulations for the present day, the preindustrial era, the early Holocene, and the Last Glacial Maximum (LGM) with a comprehensive climate model. The stability issue is an important prerequisite for reconstructions of Northern Hemisphere atmospheric circulation variability based on accumulation or precipitation proxy records from Greenland ice cores. The analysis reveals that the relationship between accumulation variability and large-scale circulation undergoes a significant seasonal cycle. As the contributions of the individual seasons to the annual signal change, annual mean accumulation variability is not necessarily related to the same atmospheric circulation patterns during the different climate states. Interestingly, within a season, local Greenland accumulation variability is indeed linked to a consistent circulation pattern, which is observed for all studied climate periods, even for the LGM. Hence, it would be possible to deduce a reliable reconstruction of seasonal atmospheric variability (e.g., for North Atlantic winters) if an accumulation or precipitation proxy were available that resolves single seasons. We further show that the simulated impacts of orbital forcing and changes in the ice sheet topography on Greenland accumulation exhibit strong spatial differences, emphasizing that accumulation records from different ice core sites regarding both interannual and long-term (centennial to millennial) variability cannot be expected to look alike since they include a distinct local signature. The only uniform signal to external forcing is the strong decrease in Greenland accumulation during glacial (LGM) conditions and an increase associated with the recent rise in greenhouse gas concentrations.

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