Changes in the Distribution of Rain Frequency and Intensity in Response to Global Warming*

2014 ◽  
Vol 27 (22) ◽  
pp. 8372-8383 ◽  
Author(s):  
Angeline G. Pendergrass ◽  
Dennis L. Hartmann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Coupled Model ◽  
Daily Rainfall ◽  
Model Intercomparison ◽  
Impact Of Climate Change ◽  
Intercomparison Project ◽  
Potential Impact ◽  
Rain Rates

Abstract Changes in the frequency and intensity of rainfall are an important potential impact of climate change. Two modes of change, a shift and an increase, are applied to simulations of global warming with models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The response to CO2 doubling in the multimodel mean of CMIP5 daily rainfall is characterized by an increase of 1% K−1 at all rain rates and a shift to higher rain rates of 3.3% K−1. In addition to these increase and shift modes of change, some models also show a substantial increase in rainfall at the highest rain rates called the extreme mode of response to warming. In some models, this extreme mode can be shown to be associated with increases in grid-scale condensation or gridpoint storms.

scholarly journals Bias-corrected climate projections for South Asia from Coupled Model Intercomparison Project-6

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Vimal Mishra ◽  
Udit Bhatia ◽  
Amar Deep Tiwari
Keyword(s):  
Climate Change ◽  
Impact Assessment ◽  
South Asia ◽  
General Circulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
River Basins ◽  
Climate Projections ◽  
Model Intercomparison ◽  
Intercomparison Project

Abstract Climate change is likely to pose enormous challenges for agriculture, water resources, infrastructure, and livelihood of millions of people living in South Asia. Here, we develop daily bias-corrected data of precipitation, maximum and minimum temperatures at 0.25° spatial resolution for South Asia (India, Pakistan, Bangladesh, Nepal, Bhutan, and Sri Lanka) and 18 river basins located in the Indian sub-continent. The bias-corrected dataset is developed using Empirical Quantile Mapping (EQM) for the historic (1951–2014) and projected (2015–2100) climate for the four scenarios (SSP126, SSP245, SSP370, SSP585) using output from 13 General Circulation Models (GCMs) from Coupled Model Intercomparison Project-6 (CMIP6). The bias-corrected dataset was evaluated against the observations for both mean and extremes of precipitation, maximum and minimum temperatures. Bias corrected projections from 13 CMIP6-GCMs project a warmer (3–5°C) and wetter (13–30%) climate in South Asia in the 21st century. The bias-corrected projections from CMIP6-GCMs can be used for climate change impact assessment in South Asia and hydrologic impact assessment in the sub-continental river basins.

Challenges in Constraining Future Change of Global Land Precipitation in CMIP6 Models

2020 ◽  
Author(s):  
June-Yi Lee ◽  
Kyung-Sook Yun ◽  
Arjun Babu ◽  
Young-Min Yang ◽  
Eui-Seok Chung ◽  
...  
Keyword(s):  
Global Warming ◽  
Emission Scenario ◽  
Coupled Model ◽  
Precipitation Change ◽  
Cmip5 Models ◽  
Model Intercomparison ◽  
Projected Change ◽  
Global Land ◽  
Intercomparison Project ◽  
Global Mean

<p><span>The Coupled Model Intercomparison Project Phase 5 (CMIP5) models have showed substantial inter-model spread in estimating annual global-mean precipitation change per one-degree greenhouse-gas-induced warming (precipitation sensitivity), ranging from -4.5</span><span>–4.2</span><span>%</span><sup><span>o</span></sup><span>C<sup>-1</sup>in the Representative Concentration Pathway (RCP) 2.6, the lowest emission scenario, to 0.2–4.0</span><span>%</span><sup><span>o</span></sup><span>C<sup>-1</sup>in the RCP 8.5, the highest emission scenario. The observed-based estimations in the global-mean land precipitation sensitivity during last few decades even show much larger spread due to the considerable natural interdecadal variability, role of anthropogenic aerosol forcing, and uncertainties in observation. This study tackles to better quantify and constrain global land precipitation change in response to global warming by analyzing the new range of Shared Socio-economic Pathway (SSP) scenarios in the </span><span>Coupled Model Intercomparison Project Phase 6 (CMIP6) compared with RCP scenarios in the CMIP5. We show that the range of projected change in annual global-mean land (ocean) precipitation by the end of the 21<sup>st</sup>century relative to the recent past (1995-2014) in the 23 CMIP6 models is over 50% (20%) larger than that in corresponding scenarios of the 40 CMIP5 models. The estimated ranges of precipitation sensitivity in four Tier-1 SSPs are also larger than those in corresponding CMIP5 RCPs. The large increase in projected precipitation change in the highest quartile over ocean is mainly due to the increased number of high equilibrium climate sensitivity (ECS) models in CMIP6 compared to CMIP5, but not over land due to different response of thermodynamic moisture convergence and dynamic processes to global warming. We further discuss key challenges in constraining future precipitation change and source of uncertainties in land precipitation change.</span></p>

scholarly journals Assessing the impacts of climate variability and climate change on biodiversity in Lake Nakuru, Kenya

2018 ◽  
Vol 8 (1) ◽  
pp. 13-24 ◽  
Author(s):  
MBOTE BETH WAMBUI ◽  
ALFRED OPERE ◽  
JOHN M. GITHAIGA ◽  
FREDRICK K. KARANJA
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Surface Area ◽  
Coupled Model ◽  
Baseline Period ◽  
Strong Positive Correlation ◽  
Model Intercomparison ◽  
Lake Nakuru ◽  
Lesser Flamingo ◽  
Intercomparison Project

Wambui MB, Opere A, Githaiga MJ, Karanja FK. 2017. Assessing the impacts of climate variability and climate change on biodiversity in Lake Nakuru, Kenya. Bonorowo Wetlands 1: 13-24. This study evaluates the impacts of the raised water levels and the flooding of Lake Nakuru and its surrounding areas on biodiversity, specifically, the phytoplankton and lesser flamingo communities, due to climate change and climate variability. The study was to review and analyze noticed climatic records from 2000 to 2014. Several methods were used to ascertain the past and current trends of climatic parameters (temperature, rainfall and evaporation), and also the physicochemical characteristics of Lake Nakuru (conductivity, phytoplankton, lesser flamingos and the lake depth). These included time series analysis, and trend analysis, so the Pearson’s correlation analysis was used to show a relationship between the alterations in lake conductivity to alterations in population estimates of the lesser flamingos and the phytoplankton. Data set extracted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) (IPCC Fifth Assessment Report (AR5) Atlas subset) models were subjected to time series analysis method where the future climate scenarios of near surface temperature, rainfall and evaporation were plotted for the period 2017 to 2100 (projection) for RCP2.6 and RCP8.5 relative to the baseline period 1971 to 2000 in Lake Nakuru were analysed. The results were used to evaluate the impact of climate change on the lesser flamingos and phytoplankton abundance. It was noticed that there was a raise in the mean annual rainfall during the study period (2009 to 2014) which brought the increment in the lake’s surface area from a low area of 31.8 km² in January 2010 to a high of 54.7 km² in Sept 2013, indicating an increment of 22.9 km² (71.92% surface area increment). Mean conductivity of the lake also lessened leading to the loss of phytoplankton on which flamingos feed making them to migrate. A strong positive correlation between conductivity and the lesser flamingo population was noticed signifying that low conductivity affects the growth of phytoplankton and since the lesser flamingos depend on the phytoplankton for their feed, this subsequently revealed that the phytoplankton density could be a notable predictor of the lesser flamingo occurrence in Lake Nakuru. There was also a strong positive correlation noticed between phytoplankton and the lesser flamingo population which confirms that feed availability is a key determining factor of the lesser flamingo distribution in the lake. It is projected that there would be an increment in temperatures, rainfall and evaporation for the period 2017 to 2100 under RCP2.6 and RCP8.5 relative to the baseline period 1971 to 2000 obtained from the Coupled Model Intercomparison Project phase 5 (CMIP5) multi-model ensemble. As a result, it is expected that the lake will further increment in surface area and depth by the year 2100 due to increased rainfall thereby affecting the populations of the lesser flamingos and phytoplankton, as the physicochemical factors of the lake will alter as well during the projected period.

scholarly journals Evaluating permafrost physics in the Coupled Model Intercomparison Project 6 (CMIP6) models and their sensitivity to climate change

2020 ◽  
Vol 14 (9) ◽  
pp. 3155-3174 ◽  
Author(s):  
Eleanor J. Burke ◽  
Yu Zhang ◽  
Gerhard Krinner
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
High Latitude ◽  
Soil Profile ◽  
Coupled Model ◽  
The Arctic ◽  
Model Intercomparison ◽  
Model Ensemble ◽  
Northern High Latitude ◽  
Intercomparison Project

Abstract. Permafrost is a ubiquitous phenomenon in the Arctic. Its future evolution is likely to control changes in northern high-latitude hydrology and biogeochemistry. Here we evaluate the permafrost dynamics in the global models participating in the Coupled Model Intercomparison Project (present generation – CMIP6; previous generation – CMIP5) along with the sensitivity of permafrost to climate change. Whilst the northern high-latitude air temperatures are relatively well simulated by the climate models, they do introduce a bias into any subsequent model estimate of permafrost. Therefore evaluation metrics are defined in relation to the air temperature. This paper shows that the climate, snow and permafrost physics of the CMIP6 multi-model ensemble is very similar to that of the CMIP5 multi-model ensemble. The main differences are that a small number of models have demonstrably better snow insulation in CMIP6 than in CMIP5 and a small number have a deeper soil profile. These changes lead to a small overall improvement in the representation of the permafrost extent. There is little improvement in the simulation of maximum summer thaw depth between CMIP5 and CMIP6. We suggest that more models should include a better-resolved and deeper soil profile as a first step towards addressing this. We use the annual mean thawed volume of the top 2 m of the soil defined from the model soil profiles for the permafrost region to quantify changes in permafrost dynamics. The CMIP6 models project that the annual mean frozen volume in the top 2 m of the soil could decrease by 10 %–40 %∘C-1 of global mean surface air temperature increase.

scholarly journals Simulated Tropical Precipitation Assessed across Three Major Phases of the Coupled Model Intercomparison Project (CMIP)

2020 ◽  
Vol 148 (9) ◽  
pp. 3653-3680 ◽  
Author(s):  
Stephanie Fiedler ◽  
Traute Crueger ◽  
Roberta D’Agostino ◽  
Karsten Peters ◽  
Tobias Becker ◽  
...  
Keyword(s):  
Climate Change ◽  
Twentieth Century ◽  
Southern Oscillation ◽  
Spatial Scales ◽  
Coupled Model ◽  
Climate Change Signal ◽  
Positive Trend ◽  
Model Intercomparison ◽  
Tropical Precipitation ◽  
Intercomparison Project

Abstract The representation of tropical precipitation is evaluated across three generations of models participating in phases 3, 5, and 6 of the Coupled Model Intercomparison Project (CMIP). Compared to state-of-the-art observations, improvements in tropical precipitation in the CMIP6 models are identified for some metrics, but we find no general improvement in tropical precipitation on different temporal and spatial scales. Our results indicate overall little changes across the CMIP phases for the summer monsoons, the double-ITCZ bias, and the diurnal cycle of tropical precipitation. We find a reduced amount of drizzle events in CMIP6, but tropical precipitation occurs still too frequently. Continuous improvements across the CMIP phases are identified for the number of consecutive dry days, for the representation of modes of variability, namely, the Madden–Julian oscillation and El Niño–Southern Oscillation, and for the trends in dry months in the twentieth century. The observed positive trend in extreme wet months is, however, not captured by any of the CMIP phases, which simulate negative trends for extremely wet months in the twentieth century. The regional biases are larger than a climate change signal one hopes to use the models to identify. Given the pace of climate change as compared to the pace of model improvements to simulate tropical precipitation, we question the past strategy of the development of the present class of global climate models as the mainstay of the scientific response to climate change. We suggest the exploration of alternative approaches such as high-resolution storm-resolving models that can offer better prospects to inform us about how tropical precipitation might change with anthropogenic warming.

scholarly journals Assessing the impacts of 1.5 °C global warming – simulation protocol of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b)

2017 ◽  
Vol 10 (12) ◽  
pp. 4321-4345 ◽  
Author(s):  
Katja Frieler ◽  
Stefan Lange ◽  
Franziska Piontek ◽  
Christopher P. O. Reyer ◽  
Jacob Schewe ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Greenhouse Gas Emission ◽  
Scientific Basis ◽  
Economic Conditions ◽  
Impact Model ◽  
Model Intercomparison ◽  
Intergovernmental Panel ◽  
Simulation Protocol ◽  
Intercomparison Project

Abstract. In Paris, France, December 2015, the Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the Intergovernmental Panel on Climate Change (IPCC) to provide a special report in 2018 on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways. In Nairobi, Kenya, April 2016, the IPCC panel accepted the invitation. Here we describe the response devised within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to provide tailored, cross-sectorally consistent impact projections to broaden the scientific basis for the report. The simulation protocol is designed to allow for (1) separation of the impacts of historical warming starting from pre-industrial conditions from impacts of other drivers such as historical land-use changes (based on pre-industrial and historical impact model simulations); (2) quantification of the impacts of additional warming up to 1.5 °C, including a potential overshoot and long-term impacts up to 2299, and comparison to higher levels of global mean temperature change (based on the low-emissions Representative Concentration Pathway RCP2.6 and a no-mitigation pathway RCP6.0) with socio-economic conditions fixed at 2005 levels; and (3) assessment of the climate effects based on the same climate scenarios while accounting for simultaneous changes in socio-economic conditions following the middle-of-the-road Shared Socioeconomic Pathway (SSP2, Fricko et al., 2016) and in particular differential bioenergy requirements associated with the transformation of the energy system to comply with RCP2.6 compared to RCP6.0. With the aim of providing the scientific basis for an aggregation of impacts across sectors and analysis of cross-sectoral interactions that may dampen or amplify sectoral impacts, the protocol is designed to facilitate consistent impact projections from a range of impact models across different sectors (global and regional hydrology, lakes, global crops, global vegetation, regional forests, global and regional marine ecosystems and fisheries, global and regional coastal infrastructure, energy supply and demand, temperature-related mortality, and global terrestrial biodiversity).

scholarly journals Sensitivity of Crop Water Need to 2071–95 Projected Temperature and Precipitation Changes in Jamaica

2014 ◽  
Vol 18 (12) ◽  
pp. 1-17 ◽  
Author(s):  
Scott Curtis ◽  
Douglas W. Gamble ◽  
Jeff Popke
Keyword(s):  
Temperature Change ◽  
Coupled Model ◽  
Precipitation Change ◽  
Model Intercomparison ◽  
Crop Water ◽  
Temperature And Precipitation ◽  
Crop Suitability ◽  
Intercomparison Project ◽  
Potential Impact ◽  
Precipitation Changes

Abstract This study uses empirical models to examine the potential impact of climate change, based on a range of 100-yr phase 5 of the Coupled Model Intercomparison Project (CMIP5) projections, on crop water need in Jamaica. As expected, crop water need increases with rising temperature and decreasing precipitation, especially in May–July. Comparing the temperature and precipitation impacts on crop water need indicates that the 25th percentile of CMIP5 temperature change (moderate warming) yields a larger crop water deficit than the 75th percentile of CMIP5 precipitation change (wet winter and dry summer), but the 25th percentile of CMIP5 precipitation change (substantial drying) dominates the 75th percentile of CMIP5 temperature change (extreme warming). Over the annual cycle, the warming contributes to larger crop water deficits from November to April, while the drying has a greater influence from May to October. All experiments decrease crop suitability, with the largest impact from March to August.

Distributions of Tropical Precipitation Cluster Power and Their Changes under Global Warming. Part II: Long-Term Time Dependence in Coupled Model Intercomparison Project Phase 5 Models

2017 ◽  
Vol 30 (20) ◽  
pp. 8045-8059 ◽  
Author(s):  
Kevin M. Quinn ◽  
J. David Neelin
Keyword(s):  
Global Warming ◽  
High Resolution ◽  
Rain Rate ◽  
Climate Model ◽  
Coupled Model ◽  
Atmospheric Model ◽  
Department Of Energy ◽  
Model Intercomparison ◽  
Intense Storm ◽  
Intercomparison Project

Abstract Distributions of precipitation cluster power (latent heat release rate integrated over contiguous precipitating pixels) are examined in 1°–2°-resolution members of phase 5 of the Coupled Model Intercomparison Project (CMIP5) climate model ensemble. These approximately reproduce the power-law range and large event cutoff seen in observations and the High Resolution Atmospheric Model (HiRAM) at 0.25°–0.5° in Part I. Under the representative concentration pathway 8.5 (RCP8.5) global warming scenario, the change in the probability of the most intense storm clusters appears in all models and is consistent with HiRAM output, increasing by up to an order of magnitude relative to historical climate. For the three models in the ensemble with continuous time series of high-resolution output, there is substantial variability on when these probability increases for the most powerful storm clusters become detectable, ranging from detectable within the observational period to statistically significant trends emerging only after 2050. A similar analysis of National Centers for Environmental Prediction (NCEP)–U.S. Department of Energy (DOE) AMIP-II reanalysis and Special Sensor Microwave Imager and Imager/Sounder (SSM/I and SSMIS) rain-rate retrievals in the recent observational record does not yield reliable evidence of trends in high power cluster probabilities at this time. However, the results suggest that maintaining a consistent set of overlapping satellite instrumentation with improvements to SSM/I–SSMIS rain-rate retrieval intercalibrations would be useful for detecting trends in this important tail behavior within the next couple of decades.

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