2024 has been unprecedented climate challenges, including several heat domes across United States and Midwest (From melting tracks to rising alcoholism – how sport is being forced to adapt to the effects of climate change). These heat domes that trap hot air under high pressure systems led to extreme temperature in days or weeks and posing some threats to human health, agriculture, and wildlife (What is a heat dome? A meteorologist explains the weather phenomenon baking the eastern US).

_{^{Figure 1. Heat domes involve high-pressure areas that trap and heat up the air below. NOAA}}

Globally, the air temperature breached the critical 1.5celcius threshold for the first time and five years earlier, that means it accelerate the pace of climate change. For example the vulnerable region, particularly in the Caribbean and Brazil, are facing catastrophic floods that needs coordinated effort to address climate migration or adaptation (Brazil needs a new approach to climate mobility). From the various phenomena that occur, we need to find solutions by utilizing various existing aspects.

Historical data could be used to forecast weather and predicting future climate uses artificial intelligence to achieve result comparable with the best existing models ( AI-powered weather and climate models are set to change the future of forecasting ). These archives provide critical baselines that allows scientist to calculate shifts in forest, wetlands, and other key ecosystems, assessing their boarder impact on the global climate system.

^{_{Figure 2. A comparison of how NeuralGCM compares with leading models (AMIP) and real data (ERA5) at capturing climate change between 1980 and 2020. Google Research}}

With the help of new technology, like satellite imagery and AI, we can now monitor deforestation, ocean temperatures, and weather patterns with much more accuracy (We used 1,000 historical photos to reconstruct Antarctic glaciers before a dramatic collapse) . This helps us better predict what might happen in the future – from rising sea levels to changing weather and its impact on food production. As the world faces increasing challenges from higher temperatures, carbon emissions, and human activities, these advanced tools are key to understanding and addressing climate change to keep the planet’s systems in balance. since the climate changes affect the forest, forest loss that causes regional warming and drying, for example, has the potential to contribute positive carbon-climate feedback because higher air temperatures may reduce photosynthesis and increase autotropic respiration, leading to lower levels of net primary production forest cover in nearby areas (Deforestation-induced climate change reduces carbon storage in remaining tropical forests), and of course it threat the carbon storage .

The carbon storage capacity of natural systems is under severe threat from human activity and climate change. The Southern Ocean plays a vital role in absorbing excess heat and carbon dioxide, helping to moderate global temperatures The Southern Ocean – a reservoir for heat and carbon. However, warming waters and melting ice are undermining these crucial processes. Efforts like seagrass transplanting have emerged as promising solutions to enhance carbon sequestration, with seagrass meadows capable of storing carbon up to 35 times faster than tropical rainforests Seagrass—secret weapon in the fight against global heating. Technological innovations, such as underwater drones and robotics, are being employed to aid seagrass restoration efforts by mapping optimal planting sites and efficiently planting seagrass in large areas. Additionally, carbon capture and storage (CCS) technologies are being developed to directly remove CO2 from the atmosphere and store it underground or in depleted oil and gas fields. These technological advancements, alongside natural solutions, are essential in mitigating the loss of critical carbon sinks, such as shrinking saline lakes and degraded ocean ecosystems. Now the sneak peek of our natural solution based on the problems.

Our Approach

^{_{Figure 3. PLANT tool}}

So, the application is PLANT ( PLABS Seagrass Location and Analysis Network Tool) it can automatically detect the seagrass transplantation site based on your area of interest. The application also give you analysis of the detected area. The red circle define that the area isnt suitable for seagrass transplant and the green one define that the area is suitable for seagrass transplant. The analysis will tell you the score of the suitable from 0 to 2. These results demonstrate the efficacy of our Bi-LSTM model in predicting suitable seagrass transplantation sites, and achieved at 88.38% accuracy on average.

Data Summary
labels	training set	testing set	total
class 0	2488	1066	3554
class 2	2487	1066	3553

The Bi-LSTM approach was introduced for identifying and evaluating optimal sites for seagrass trans- plantation, comparing it with Echo State Networks (ESN) and One-Dimensional Convolutional Neural Networks (CNN-1D). The Bi-LSTM model, trained over 10 epochs and achieved an initial training and validation accuracy are 98.75% and 99.98% respectively, also training and validation loss are 0.0326 and 0.0112 respectively, demonstrating its capability to effectively learn and generalize from sequential data.