### Apache Airflow version

2.2.1 (latest released)

### Operating System

PRETTY_NAME="Debian GNU/Linux 10 (buster)

### Versions of Apache Airflow Providers

apache-airflow-providers-ftp==2.0.1
apache-airflow-providers-http==2.0.1
apache-airflow-providers-imap==2.0.1
apache-airflow-providers-sqlite==2.0.1

### Deployment

Docker-Compose

### Deployment details

_No response_

### What happened

Backfilling via catchup=True leads to missing DagRuns. 

See reproduction steps for full details

### What you expected to happen

_No response_

### How to reproduce

Note, this is an issue which we have experienced in our production environment, with a much more complicated DAG. Below are the reproduction steps using breeze.

1. Setup ./breeze environment with the below config modifications
2. Create a simple DAG, with dummy tasks in it (see below example)
2. Set a `start_date` in the past
3. Set `catchup=True`
4. Unpause the DAG
5. Catch up starts and if you view the tree view, you have the false impression that everything has caught up correctly. 
6. However, access the calendar view, you can see the missing DagRuns. 

**Breeze Config**
```
export DB_RESET="true"
export START_AIRFLOW="true"
export INSTALL_AIRFLOW_VERSION="2.2.1"
export USE_AIRFLOW_VERSION="2.2.1"
```

**Dummy DAG**
```
from datetime import datetime
from airflow import DAG
from airflow.operators.dummy import DummyOperator

dag = DAG(
    dag_id="temp_test",
    schedule_interval="@daily",
    catchup=True,
    start_date=datetime(2021, 8, 1),
    max_active_tasks=10,
    max_active_runs=5,
    is_paused_upon_creation=True,
)

with dag:
    task1 = DummyOperator(task_id="task1")
    task2 = DummyOperator(task_id="task2")
    task3 = DummyOperator(task_id="task3")
    task4 = DummyOperator(task_id="task4")
    task5 = DummyOperator(task_id="task5")

    task1 >> task2 >> task3 >> task4 >> task5
```

**Results**
<img width="1430" alt="tree_view" src="https://user-images.githubusercontent.com/10559757/140715465-6bc3831c-d71c-4025-bcde-985010ab31f8.png">

<img width="1435" alt="calendar_view" src="https://user-images.githubusercontent.com/10559757/140715467-1a1a5c9a-3eb6-40ff-8720-ebe6db999028.png">


### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

airflow/jobs/scheduler_job.py
from airflow.models.dagbag import DagBag
from airflow.models.dagrun import DagRun
from airflow.models.serialized_dag import SerializedDagModel
from airflow.models.taskinstance import SimpleTaskInstance, TaskInstance, TaskInstanceKey
from airflow.stats import Stats
from airflow.ti_deps.dependencies_states import EXECUTION_STATES
from airflow.utils import timezone
from airflow.utils.callback_requests import DagCallbackRequest, TaskCallbackRequest
from airflow.utils.event_scheduler import EventScheduler
from airflow.utils.retries import MAX_DB_RETRIES, retry_db_transaction, run_with_db_retries
from airflow.utils.session import create_session, provide_session
from airflow.utils.sqlalchemy import is_lock_not_available_error, prohibit_commit, skip_locked, with_row_locks
from airflow.utils.state import DagRunState, State, TaskInstanceState
from airflow.utils.types import DagRunType
TI = models.TaskInstance
DR = models.DagRun
DM = models.DagModel
def _is_parent_process():
    """
    Returns True if the current process is the parent process. False if the current process is a child
    process started by multiprocessing.
    """
    return multiprocessing.current_process().name == 'MainProcess'
class SchedulerJob(BaseJob):
    """
    This SchedulerJob runs for a specific time interval and schedules the jobs
    that are ready to run. It figures out the latest runs for each
    task and sees if the dependencies for the next schedules are met.
    If so, it creates appropriate TaskInstances and sends run commands to the
    executor. It does this for each task in each DAG and repeats.