Changes in future precipitation mean and variability across scales

2020 ◽  
pp. 1-55
Author(s):  
Kevin Schwarzwald ◽  
Andrew Poppick ◽  
Maria Rugenstein ◽  
Jonah Bloch-Johnson ◽  
Jiali Wang ◽  
...  
Keyword(s):  
Regional Scale ◽  
Precipitation Variability ◽  
Climate Projections ◽  
Rainfall Events ◽  
Spatial And Temporal Scales ◽  
Multiplicative Shift ◽  
The Tropics ◽  
Multiplicative Mean ◽  
Small Additive ◽  
Additive Term

AbstractChanges in precipitation variability can have large societal consequences, whether at the short timescales of flash floods or the longer timescales of multi-year droughts. Recent studies have suggested that in future climate projections, precipitation variability rises more steeply than does its mean, leading to concerns about societal impacts. This work evaluates changes in mean precipitation over a broad range of spatial and temporal scales using a range of models from high-resolution regional simulations to millennial-scale global simulations. Results show that changes depend on the scale of aggregation and involve strong regional differences. On local scales that resolve individual rainfall events (hours and tens of kilometers), changes in precipitation distributions are complex and variances rise substantially more than means, as is required given the well-known disproportionate rise in precipitation intensity. On scales that aggregate across many events, distributional changes become simpler and variability changes smaller. At regional scale, future precipitation distributions can be largely reproduced by a simple transformation of present-day precipitation involving a multiplicative shift and a small additive term. The “extra” broadening is negatively correlated with changes in mean precipitation: in strongly “wetting” areas, distributions broaden less than expected from a simple multiplicative mean change; in “drying” areas, distributions narrow less. Precipitation variability changes are therefore of especial concern in the subtropics, which tend to dry under climate change. Outside the tropics, variability changes are similar on timescales from days to decades, i.e. show little frequency dependence. This behavior is highly robust across models, suggesting it may stem from some fundamental constraint.

Differential Credibility of Climate Modes in CMIP6

2021 ◽  
pp. 1
Author(s):  
Jacob Coburn ◽  
S.C. Pryor
Keyword(s):  
Southern Oscillation ◽  
Probability Distributions ◽  
Critical Role ◽  
Regional Scale ◽  
Southern Annular Mode ◽  
Climate Projections ◽  
Annular Mode ◽  
Climate Modes ◽  
First Order ◽  
Skill Scores

AbstractThis work quantitatively evaluates the fidelity with which the Northern Annular Mode (NAM), Southern Annular Mode (SAM), Pacific-North American pattern (PNA), El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) and the first-order mode interactions are represented in Earth System Model (ESM) output from the CMIP6 archive. Several skill metrics are used as part of a differential credibility assessment (DCA) of both spatial and temporal characteristics of the modes across ESMs, ESM families and specific ESM realizations relative to ERA5. The spatial patterns and probability distributions are generally well represented but skill scores that measure the degree to which the frequencies of maximum variance are captured are consistently lower for most ESMs and climate modes. Substantial variability in skill scores manifests across realizations from individual ESMs for the PNA and oceanic modes. Further, the ESMs consistently overestimate the strength of the NAM-PNA first-order interaction and underestimate the NAM-AMO connection. These results suggest that the choice of ESM and ESM realizations will continue to play a critical role in determining climate projections at the global and regional scale at least in the near-term.

scholarly journals Land–atmosphere interactions in the tropics

2019 ◽  
Author(s):  
Pierre Gentine ◽  
Adam Massmann ◽  
Benjamin R. Lintner ◽  
Sayed Hamed Alemohammad ◽  
Rong Fu ◽  
...  
Keyword(s):  
Land Surface ◽  
Deep Convection ◽  
Lower Troposphere ◽  
Surface Fluxes ◽  
Surface Radiation ◽  
Spatial And Temporal Scales ◽  
Wide Range ◽  
Shallow Clouds ◽  
The Tropics ◽  
The Impact

Abstract. The continental tropics play a leading role in the terrestrial water and carbon cycles. Land–atmosphere interactions are integral in the regulation of surface energy, water and carbon fluxes across multiple spatial and temporal scales over tropical continents. We review here some of the important characteristics of tropical continental climates and how land–atmosphere interactions regulate them. Along with a wide range of climates, the tropics manifest a diverse array of land–atmosphere interactions. Broadly speaking, in tropical rainforests, light and energy are typically more limiting than precipitation and water supply for photosynthesis and evapotranspiration; whereas in savanna and semi-arid regions water is the critical regulator of surface fluxes and land–atmosphere interactions. We discuss the impact of the land surface, how it affects shallow clouds and how these clouds can feedback to the surface by modulating surface radiation. Some results from recent research suggest that shallow clouds may be especially critical to land–atmosphere interactions as these regulate the energy budget and moisture transport to the lower troposphere, which in turn affects deep convection. On the other hand, the impact of land surface conditions on deep convection appear to occur over larger, non-local, scales and might be critically affected by transitional regions between the climatologically dry and wet tropics.

scholarly journals An Assessment of Social and Physical Vulnerability to Hydroclimate Extremes in Appalachia

2021 ◽  
Author(s):  
Leah R. Handwerger ◽  
Jennifer R. Runkle ◽  
Ronald Leeper ◽  
Elizabeth Shay ◽  
Kara Dempsey ◽  
...  
Keyword(s):  
Social Vulnerability ◽  
Scientific Community ◽  
Vulnerability Index ◽  
Precipitation Variability ◽  
Mitigation Strategies ◽  
Climate Projections ◽  
Social Vulnerability Index ◽  
Physical Vulnerability ◽  
Vulnerable Communities ◽  
Vulnerability Indicators

Abstract Appalachia is a cultural region in the southern and central Appalachian Mountains that lags behind the nation in several social vulnerability indicators. Climate projections over this region indicate that precipitation variability will increase in both severity and frequency in future decades, suggesting that the occurrence of natural hazards related to hydroclimate extremes will also increase. The objective of this study was to investigate the spatiotemporal patterns of drought and precipitation and determine how trends overlap with vulnerable communities across Appalachia. The study utilized trend analysis through Mann-Kendall calculations and a Social Vulnerability Index, resulting in a bivariate map that displays areas most susceptible to adverse effects from hydroclimate extremes. Results show the southwestern portion of the region as most vulnerable to increased precipitation, and the central-southeast most vulnerable to an increase in drought-precipitation variability. This study is among the first to utilize the boundaries defined by the Appalachian Regional Commission from a climatological perspective, allowing findings to reach audiences outside the scientific community and bring more effective mitigation strategies that span from the local to federal levels.

scholarly journals Impact of anthropogenic activities on global land oxygen flux

2019 ◽  
Author(s):  
Xiaoyue Liu ◽  
Jianping Huang ◽  
Jiping Huang ◽  
Changyu Li ◽  
Lei Ding
Keyword(s):  
Fossil Fuel ◽  
Anthropogenic Activities ◽  
Atmospheric Oxygen ◽  
Regional Scale ◽  
Central Africa ◽  
Heterotrophic Soil Respiration ◽  
Habitable Planet ◽  
Higher Temperature ◽  
Dynamic Description ◽  
The Tropics

Abstract. Atmospheric oxygen (O2) is one of the predominant features that enable Earth as a habitable planet for active and diverse biology. However, observations since the late 1980s indicate that O2 content in the atmosphere is falling steadily at part-per-million level. Although a scientific consensus has emerged that the current decline is generally attributed to the combustion of fossil fuel, a quantitative assessment of the anthropogenic impact on the O2 cycle on both global and regional scale is currently lacking. This paper quantifies the anthropogenic and biological O2 flux over land and provides a quantitative and dynamic description of land O2 budget under impacts of human activities on grid scale. It is found that total anthropogenic O2 flux over land has risen from 35.6 Gt/yr in 2000 to 46.0 Gt/yr in 2013, while the compensation from land (11.5 Gt/yr averaged from 2000 to 2013) displays a faint increase during the same period. High anthropogenic fluxes mainly occur in Eastern Asia, India, North America and Europe caused by fossil fuel combustion and in Central Africa caused by wildfire. Due to strong heterotrophic soil respiration under higher temperature conditions, the positive O2 flux in the tropics is not significant. Instead, boreal forest and Tibetan plateau become the most important sources of atmospheric O2 in the Anthropocene. The anthropogenic oxygen consumption data are publicly available online at https://doi.org/10.1594/PANGAEA.899167.

scholarly journals Dry and moist dynamics shape regional patterns of extreme precipitation sensitivity

2020 ◽  
Vol 117 (16) ◽  
pp. 8757-8763 ◽  
Author(s):  
Ji Nie ◽  
Panxi Dai ◽  
Adam H. Sobel
Keyword(s):  
Global Warming ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Climate Model ◽  
Regional Scale ◽  
Vertical Motion ◽  
Precipitable Water ◽  
Small Scale ◽  
Climate Projections ◽  
Regional Patterns

Responses of extreme precipitation to global warming are of great importance to society and ecosystems. Although observations and climate projections indicate a general intensification of extreme precipitation with warming on global scale, there are significant variations on the regional scale, mainly due to changes in the vertical motion associated with extreme precipitation. Here, we apply quasigeostrophic diagnostics on climate-model simulations to understand the changes in vertical motion, quantifying the roles of dry (large-scale adiabatic flow) and moist (small-scale convection) dynamics in shaping the regional patterns of extreme precipitation sensitivity (EPS). The dry component weakens in the subtropics but strengthens in the middle and high latitudes; the moist component accounts for the positive centers of EPS in the low latitudes and also contributes to the negative centers in the subtropics. A theoretical model depicts a nonlinear relationship between the diabatic heating feedback (α) and precipitable water, indicating high sensitivity of α (thus, EPS) over climatological moist regions. The model also captures the change of α due to competing effects of increases in precipitable water and dry static stability under global warming. Thus, the dry/moist decomposition provides a quantitive and intuitive explanation of the main regional features of EPS.

scholarly journals RainFARM: Rainfall Downscaling by a Filtered Autoregressive Model

2006 ◽  
Vol 7 (4) ◽  
pp. 724-738 ◽  
Author(s):  
Nicola Rebora ◽  
Luca Ferraris ◽  
Jost von Hardenberg ◽  
Antonello Provenzale
Keyword(s):  
Random Field ◽  
Autoregressive Model ◽  
Gaussian Random Field ◽  
Statistical Properties ◽  
The Other ◽  
Small Scale ◽  
Intense Rainfall ◽  
Rainfall Events ◽  
The Tropics ◽  
Meteorological Models

Abstract A method is introduced for stochastic rainfall downscaling that can be easily applied to the precipitation forecasts provided by meteorological models. Our approach, called the Rainfall Filtered Autoregressive Model (RainFARM), is based on the nonlinear transformation of a Gaussian random field, and it conserves the information present in the rainfall fields at larger scales. The procedure is tested on two radar-measured intense rainfall events, one at midlatitude and the other in the Tropics, and it is shown that the synthetic fields generated by RainFARM have small-scale statistical properties that are consistent with those of the measured precipitation fields. The application of the disaggregation procedure to an example meteorological forecast illustrates how the method can be implemented in operational practice.

scholarly journals Propagation of Strong Rainfall Events from Southeastern South America to the Central Andes

2015 ◽  
Vol 28 (19) ◽  
pp. 7641-7658 ◽  
Author(s):  
Niklas Boers ◽  
Henrique M. J. Barbosa ◽  
Bodo Bookhagen ◽  
José A. Marengo ◽  
Norbert Marwan ◽  
...  
Keyword(s):  
South America ◽  
Wave Train ◽  
Monsoon Season ◽  
Central Andes ◽  
High Temporal Resolution ◽  
Spatiotemporal Resolution ◽  
Rainfall Events ◽  
Low Level ◽  
Societal Relevance ◽  
The Tropics

Abstract Based on high-spatiotemporal-resolution data, the authors perform a climatological study of strong rainfall events propagating from southeastern South America to the eastern slopes of the central Andes during the monsoon season. These events account for up to 70% of total seasonal rainfall in these areas. They are of societal relevance because of associated natural hazards in the form of floods and landslides, and they form an intriguing climatic phenomenon, because they propagate against the direction of the low-level moisture flow from the tropics. The responsible synoptic mechanism is analyzed using suitable composites of the relevant atmospheric variables with high temporal resolution. The results suggest that the low-level inflow from the tropics, while important for maintaining sufficient moisture in the area of rainfall, does not initiate the formation of rainfall clusters. Instead, alternating low and high pressure anomalies in midlatitudes, which are associated with an eastward-moving Rossby wave train, in combination with the northwestern Argentinean low, create favorable pressure and wind conditions for frontogenesis and subsequent precipitation events propagating from southeastern South America toward the Bolivian Andes.

scholarly journals Remote sensing of cloud top pressure/height from SEVIRI: analysis of ten current retrieval algorithms

2014 ◽  
Vol 7 (9) ◽  
pp. 2839-2867 ◽  
Author(s):  
U. Hamann ◽  
A. Walther ◽  
B. Baum ◽  
R. Bennartz ◽  
L. Bugliaro ◽  
...  
Keyword(s):  
Measurement Techniques ◽  
Single Layer ◽  
Correlation Coefficients ◽  
Trade Wind ◽  
Convective System ◽  
Climate Projections ◽  
Data Sets ◽  
Retrieval Algorithms ◽  
The Tropics ◽  
Cloud Top Pressure

Abstract. The role of clouds remains the largest uncertainty in climate projections. They influence solar and thermal radiative transfer and the earth's water cycle. Therefore, there is an urgent need for accurate cloud observations to validate climate models and to monitor climate change. Passive satellite imagers measuring radiation at visible to thermal infrared (IR) wavelengths provide a wealth of information on cloud properties. Among others, the cloud top height (CTH) – a crucial parameter to estimate the thermal cloud radiative forcing – can be retrieved. In this paper we investigate the skill of ten current retrieval algorithms to estimate the CTH using observations from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG). In the first part we compare ten SEVIRI cloud top pressure (CTP) data sets with each other. The SEVIRI algorithms catch the latitudinal variation of the CTP in a similar way. The agreement is better in the extratropics than in the tropics. In the tropics multi-layer clouds and thin cirrus layers complicate the CTP retrieval, whereas a good agreement among the algorithms is found for trade wind cumulus, marine stratocumulus and the optically thick cores of the deep convective system. In the second part of the paper the SEVIRI retrievals are compared to CTH observations from the Cloud–Aerosol LIdar with Orthogonal Polarization (CALIOP) and Cloud Profiling Radar (CPR) instruments. It is important to note that the different measurement techniques cause differences in the retrieved CTH data. SEVIRI measures a radiatively effective CTH, while the CTH of the active instruments is derived from the return time of the emitted radar or lidar signal. Therefore, some systematic differences are expected. On average the CTHs detected by the SEVIRI algorithms are 1.0 to 2.5 km lower than CALIOP observations, and the correlation coefficients between the SEVIRI and the CALIOP data sets range between 0.77 and 0.90. The average CTHs derived by the SEVIRI algorithms are closer to the CPR measurements than to CALIOP measurements. The biases between SEVIRI and CPR retrievals range from −0.8 km to 0.6 km. The correlation coefficients of CPR and SEVIRI observations vary between 0.82 and 0.89. To discuss the origin of the CTH deviation, we investigate three cloud categories: optically thin and thick single layer as well as multi-layer clouds. For optically thick clouds the correlation coefficients between the SEVIRI and the reference data sets are usually above 0.95. For optically thin single layer clouds the correlation coefficients are still above 0.92. For this cloud category the SEVIRI algorithms yield CTHs that are lower than CALIOP and similar to CPR observations. Most challenging are the multi-layer clouds, where the correlation coefficients are for most algorithms between 0.6 and 0.8. Finally, we evaluate the performance of the SEVIRI retrievals for boundary layer clouds. While the CTH retrieval for this cloud type is relatively accurate, there are still considerable differences between the algorithms. These are related to the uncertainties and limited vertical resolution of the assumed temperature profiles in combination with the presence of temperature inversions, which lead to ambiguities in the CTH retrieval. Alternative approaches for the CTH retrieval of low clouds are discussed.

scholarly journals Regional aspects of global climate change simulations : Validation and assessment of climate response over Indian monsoon region to transient increase of greenhouse gases and sulfate aerosols

MAUSAM ◽  
2021 ◽  
Vol 52 (1) ◽  
pp. 229-244
Author(s):  
K. RUPA KUMAR ◽  
R. G. ASHRIT
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
General Circulation ◽  
Regional Scale ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Change Scenario ◽  
Climate Projections ◽  
Sulfate Aerosols ◽  
Monsoon Climate

The regional climatic impacts associated with global climatic change and their assessment are very important since agriculture, water resources, ecology etc., are all vulnerable to climatic changes on regional scale. Coupled Atmosphere-Ocean general circulation model (AOGCM) simulations provide a range of scenarios, which can be used, for the assessment of impacts and development of adaptive or mitigative strategies. Validation of the models against the observations and establishing the sensitivity to climate change forcing are essential before the model projections are used for assessment of possible impacts. Moreover model simulated climate projections are often of coarse resolution while the models used for impact assessment, (e.g. crop simulation models, or river runoff models etc.) operate on a higher spatial resolution. This spatial mismatch can be overcome by adopting an appropriate strategy of downscaling the GCM output.   This study examines two AOGCM (ECHAM4/OPYC3 and HadCM2) climate change simulations for their performance in the simulation of monsoon climate over India and the sensitivity of the simulated monsoon climate to transient changes in the atmospheric concentrations of greenhouse gases and sulfate aerosols. The results show that the two models simulate the gross features of climate over India reasonably well. However the inter-model differences in simulation of mean characteristics, sensitivity to forcing and in the simulation of climate change suggest need for caution. Further an empirical downscaling approach in used to assess the possibility of using GCM projections for preparation of regional climate change scenario for India.

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