Climate Change: questions and answers part 5

Q: What are the key assumptions on which the IPCC SRES scenarios are based? What are the main differences between the A1FI and B2 scenarios? What is the principal difference between the IPCC SRES (pre-2012) and RCP (AR5) scenarios?

Ans:

A1FI: Deals with  rapid economic growth in global context and rapid introductions of new and more efficient technologies,with emphasis on fossil fuel intensive,while

B2:  Deals with an emphasis on local solutions to economic and environmental sustainability having more environmental and original approaches.

The principal difference between the IPCC SRES (pre-2012) and RCP (AR5) scenarios:

1. The IPCC SRES (pre-2012), scenarios had socioeconomic storylines but climate mitigation options were not included as in case of RCP (AR5) scenario. 

2. RCP (AR5) scenario intended to provide a flexible, interactive, and iterative approach to climate change scenarios which were not included in IPCC SRES (pre-2012).

3. In  RCP (AR5) scenario, socioeconomic scenarios, emissions, and subsequent radiative forcing pathways were  linked to one,which were absent in IPCC SRES (pre-2012) .

4. All RCPs adopted stringent air pollution mitigation policies and thus have much lower tropospheric ozone and aerosol  abundances than the SRES scenarios, which ignored  the role of air quality regulations.

Q: Why is it important to be able to downscale climate models to spatial scales below about 50 km?

Ans: It important  to downscale climate models to spatial scales below about 50 km,because Global Climate Models (GCMs) used for climate studies and climate projections, run at coarse spatial resolution (in 2012, typically of the order 50 kilometres (31 mi),and were unable to resolve important sub-grid scale features such as clouds and topography. As a result GCM output can not be used for local impact studies.
To overcome this problem downscaling methods were used to obtain local-scale weather and climate, particularly at the surface level, from regional-scale atmospheric variables that are provided by GCMs.

Q: If you know the physical laws for how a system changes over time, in what ways could this system be unpredictable? What is this relevance of this to climate change modelling?

Ans: If I knew that the physical laws for  a system changes over time, then the system could be unpredictable in a number of ways:

1. It's a complex system that intervenes with the physical law having time delays.

2. Over passage of time,there could be non linear interactions within the system.

3. There might be loopholes in the feedback system.

4. Just because the system might be deterministic,it doesn't guarantee its predictability to the future.

The relevance of the above to climate change modelling are:

1. weather can be predicted.

2. Catastrophic shifts in the ecosystems can be predicted over time.

3. Ocean ecosystem can be predicted.

Q: Why can it be helpful to model a system at the level of individual agents instead of only considering population averages in the model? Why wouldn't both approaches give the same answer?

Ans: It can be helpful to model a system at the level of individual agents instead of only considering population averages in the model because,it's a complex system and we often need to use techniques like agent based modelling to understand how system behaves,the ways in which agents are being connected to each other and how this connection would ultimately effect the system behavior.

Both approaches would not give the same answer because Individual agents probability of occurrence in a population set would be different from those of when we consider the population averages.i.e the in case of individual agents the probability of occurrence would be considered that are most likely to occur while in population average,the average probabilities would be considered to determine the result.

References:

• https://sites.google.com/view/rk-srivastava/publications

What should be baseline/reference period for climate change impact simulation ?

Well, This is look hot topic for current time. In climate change studies, baseline year period is more important and necessary as it considered as reference period to assess the impact of future climate change. But the baseline year period  is suggested 30 years time periods of 1960-1990 by WMO (WMO, 2007). According to IPCC definition A baseline period is needed to define the observed climate with which climate change information is usually combined to create a climate scenario. Initially, IPCC suggested to use time period 1931 to 1950 then 1951 to 1980 thereafter 1961 to 1990 for climate change studies. And the reason is later periods (1961 to 1990) are likely to have larger anthropogenic trends embedded in the climate data, especially the effects of sulfate aerosols over regions such as Europe and eastern USA.

After regularly update the recommended period is now 1981-2010 by WMO (Page 1) and in future, WMO will use time period 1991-2020. However, IPCC used 20 years of period 1986-2005 to compare the climate change (Table  3.1) and will use the years 1995–2014 in its Sixth Assessment Report. But what I remember GCM’s input data were 1850-2005 and afterwards year periods 2005 to 2100 are GCM’s output and most of studies considered time period 1970-2004 as baseline period.

Effect of different baseline period of US

According to NOAA blog "The influence of long-term global warming is obvious: the earliest map in the series has the most widespread and darkest blues, and the most recent map has the most widespread and darkest reds. Today, the normal annual temperatures across the country are warmer than the 20th-century average virtually everywhere. From 1901-1930, the annual average temperature was mostly colder than the 20th-century average"

Adaptation strategy for maize crop

 Dear Friends,

I have noticed that the recently published most manuscript showed nitrogen and irrigation managements are the best adaptation strategy to cope with climate change. Unfortunately, they create environmental problem rather than increasing crop yield.

Identification of the appropriate management strategy and technologies to attain the aforesaid objective is critical. To head towards zero waste with agriculture while maintaining environmental sustainability in the future is even more daunting. Substantially, the environmental management systems can be balanced by eco-friendly practices in agriculture (manage the sowing dates), extended production responsibilities (planning for sowing management effects), and improved crop handling (reduction in water wastage). Thus, a balanced economy can be achieved by holistic and systematic thinking (crop modelling), toxic substances reduction/elimination (application of fewer fertilizers) leading to waste reduction. Apart from this, farmer awareness with the policies and ongoing research can also help in strategic management with agriculture, and thereby environment can easily be collaborated and outreached. (Srivastava et al., 2022)"

N Fertilizer

 High application of N fertilizers can create environment problem as when runoff occurs those fertilizers will become pollutant. Also, ammonia emissions will be higher due to dry surface because of extreme weather. Ammonia considered as green house gas which increase the climate change. Hence, in any condition, Fertilizer can not be good adaptation strategy. 

Irrigation

Further, irrigation will increase due to extreme temperature or warming climate. But, ground water is declining due to high demand for drinking and agriculture is the only sector which consume a lot of water. Hence, irrigation is also not the good adaptation strategy to cope with climate change.

Sowing dates

Other adaptation such as evolution of new variety is expensive. Hence, shifting sowing date can be a good adaptation strategy. But shifting sowing date is a local based management in India. As India is a diverse country and management can vary at regional level too. Hence local management based adaption strategy can be useful.  Moreover, the estimation of crop productivity was more significant on a local scale rather than on a regional one.  Implementing local approaches to improve the adaptation strategies through crop-climate modelling for the farmers and stakeholders. Hence, effective adaptation strategies need to be evaluated on a local basis first than on a regional basis to reduce the impact of climate change. Thus, modelling of adaptation strategies will be locally relevant for a longer term to be resilient to future climate change.

Sowing date as adaptation Strategy

Recent study evaluated shifting sowing dates as adaptation strategy for maize crop in Eastern India. For that Four RCP's (2.6, 4.5, 6.0 and 8.5) were used  for the year period 2021-50 and 2051-2081 of 17 GCMs. Methodology is presented below.

Below figure (a and b) shows the evaluation of sowing dates to simulated average grain yield for all the sites with current climate (baseline) under rainfed and irrigated seasons using violin plot for all scenarios. Moreover, the coefficients of variables were estimated to analyze the performance of the sowing dates under rainfed and irrigated seasons.

Figure also shows that early sowing dates 25 Dec and 5 Jan are suitable for all the RCP scenarios of CMIP5 climate projections and gave higher yield under both time periods. Whilst, the late sowing dates (25 Jan and 5 Feb) were unsuitable due to high uncertainty, low grain yield than the baseline, and earlier sowing dates for both the time periods. The sowing date (15 Jan) gave a notable estimated yield but the yield deviation was high for both time slice 2050s and 2080s in all the RCP scenarios.

How shifting sowig dates affects

Thus, the early sowing dates faced a dry spell while the late sowing dates faced high rainfall, thereby indicating crop failure in both cases. The shifting sowing dates can alter the grain filling period which is beneficial for the accumulation of dry matter in the grain. In addition, the distribution of rainfall within the crop growing period can alter the effects of the temperature. Moreover, increasing CO2 can harm crop yield if the maximum photosynthesis rate is exceeded.

Above figure indicates that the earlier sowing date 30 May and late sowing date 30 June under rainfed condition, while earlier sowing dates 25 December under irrigated condition showed less reduction in grain yield in both historic and future periods. Moreover, shifting sowing dates had a larger influence in the future periods than the historic period for the Purlia and Birbhum districts, while West Medinipur and Bankura districts, earlier sowing dates showed less reduction in grain yield in comparison to the delayed sowing dates under irrigated condition. Furthermore, late sowing date 30 June had a larger influence in future periods than the historic one, while in West Medinipur district, earlier sowing dates are more influential under rainfed conditions. Thus, under the rainfed condition, the earlier sowing dates (30 May and 30 June) show a reduction effect in the grain yield in future periods in all the RCPs for all districts except the West Medinipur. 

However, delaying the sowing period until 10 July had a negative effect for the West Medinipur and Bankura districts specifically. Under irrigated condition particularly, with the late sowing dates a consistent grain yield reduction was observed across all the districts in all scenarios and time periods. Also, all the sowing dates showed a reduction in yield with increasing RCP especially for RCP 8.5, and the time period 2080s had more impact on the grain yield than 2050s in comparison to the historic period. 

Is it beneficial as a management ?

• Well, first of all, well calibrated model needed because of reliability and for that strong data required. 
• The sowing date (5 Jan) was suitable for the time slice 2021–50 in all the RCP scenario, while earlier sowing date (25 Dec) was found to be suitable in the time slice period of 2051–80 with RCPs 8.5 for the irrigated season. 
• The sowing dates, 10 and 20 Jun were effective in RCPs 2.6, and 4.5 for the time slice 2051–2080 under rainfed season. 
• Effectiveness of late sowing dates was higher in RCPs 6.0, and 8.5 for both the time periods under rainfed season. 
• The changing sowing dates can reduce the effect of temperature on sensitive crop growth stage in irrigated season, while it can help to meet the precipitation on the sensitive crop growth stages. 
• Henceforth, the shifting of sowing dates can be adopted effectively and economically with less imports to reduce the detrimental climate change impact.

References:

https://www.sciencedirect.com/science/article/abs/pii/S0959652622002402?via%3Dihub

https://sites.google.com/view/rk-srivastava/home

Climate Change: questions and answers part 1

Dear Friends, 

Climate change is now occurring all over world in a different way. Some countries are facing as extreme events such as extreme temperature, high intensity of rainfall and changed rainfall pattern. Some countries are also facing see level rises, high frequency of flood, melting ices and breaking icebergs, high frequency of wild fires due to rising temperature and these events are abruptly increasing and observed. Recently,  one report has been published in dw news "how melting icebergs in all over world" and weather warning in Europe has been increase as Europe now facing unusual stroms. Moreover, one report was published about drying Rhine river due to climate change and there are several incidents in India. However, Climate change is not a new topic. It was happening in historic time and several civilization was over due to extreme events.

Climate change

Further, climate change is long term process and it can not be over in one day. That can stop by spreading awareness about environment and how climate change is happening. There are several programs and research already ongoing funded by several agencies such as FAO, WHO, UNFCC, IPCC and local governments. Some time they also release some regulation regarding the climate change extreme and warnings.

Here, I am presenting some questions and answers which i submitted during one training course " Building resilience to climate change courses I and II" by united nation university Japan at IIT Kharagpur in year 2015. Hopefully, it will to help to under stand climate change. If any you have any question, Please let me know in comment section. Feel free for comments and suggestion.

NOAA logo

• Atmosphere has been mostly directly affected by human activities.Atmosphere contain the green house gases and these gases directly affect the atmosphere.

• There is rapid increase in the production of green house gases with increase in the no. of industries and also by methane gas in the atmosphere.

• Increase in radiative forcing from human activity is attributable mainly to increased atmospheric carbon dioxide levels. CO2 is produced by fossil fuel burning and other activities such as cement production and tropical deforestation.

• The atmosphere contains several trace gases which absorb and emit infrared radiation. These so-called greenhouse gases absorb infrared radiation, emitted by the Earth’s surface.

• The action of carbon dioxide and other greenhouse gases in trapping infrared radiation is called the greenhouse effect.

• Human activity since the Industrial Revolution has increased the amount of greenhouse gases in the atmosphere, leading to increased radiative forcing from CO2, methane, tropospheric ozone, CFCs and nitrous oxide.

Question and answer:

Q: Identify the 6 main components of the biophysical Earth system. Which one do you think has the most important role in determining global climate? Which of these are likely to have been most directly affected by human activities during the last thousand years?

Ans: The 6 main components of the biophysical Earth system is:

1. Lithosphere

2. Hydrosphere

3. Cryosphere

4. Atmosphere

5. Troposphere

6. Stratosphere

Since atmosphere contains the green house gases and is characterized by temperature, wind, precipitation, clouds and other weather elements, so atmosphere has the most important role in determining global climate.